Index (JDistlib 0.10.0-SNAPSHOT API)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

a - Variable in class jdistlib.Arcsine
a - Variable in class jdistlib.Beta
a - Variable in class jdistlib.HyperGeometric.RandomState
a - Variable in class jdistlib.Kumaraswamy
a - Variable in class jdistlib.NonCentralBeta
a - Variable in class jdistlib.Uniform
aad(double[]) - Static method in class jdistlib.math.VectorMath: Average Absolute Deviation (AAD) (i.e., mean(abs(e - median(e))))
About the Mersenne Twister - Search tag in class jdistlib.rng.MersenneTwister: Section
About the Mersenne Twister - Search tag in class jdistlib.rng.MersenneTwisterSafe: Section
About this Version - Search tag in class jdistlib.rng.MersenneTwister: Section
About this Version - Search tag in class jdistlib.rng.MersenneTwisterSafe: Section
abs() - Method in class jdistlib.math.Complex
abserr - Variable in class jdistlib.math.IntegrationResult
absoluteError - Variable in class jdistlib.CopulaMeasureResult
absoluteError - Variable in class jdistlib.MultivariateProbabilityResult: Replication-based absolute error indicator.
absoluteMcse() - Method in class jdistlib.inference.PrecisionGoal
absoluteMcse(double) - Method in class jdistlib.inference.PrecisionGoal.Builder
AbsoluteMomentAnalysis - Class in jdistlib: Estimate and independent left/right convergence evidence for E[|X|^p].
absoluteTolerance - Variable in class jdistlib.inference.solver.OdeSolver.Options
absoluteTolerance - Variable in class jdistlib.inference.solver.StiffOdeSolver.Options
absoluteTolerance - Variable in class jdistlib.MultivariateProbabilityOptions
accelerated() - Method in class jdistlib.accelerator.ComputeSelection
accelerated() - Method in class jdistlib.accelerator.ExecutionPlan
AcceleratedLogisticRegression - Class in jdistlib.inference: Device-resident batched logistic-regression posterior with a spherical normal prior.
AcceleratedLogisticRegression(ComputeBackend, double[][], double[], double) - Constructor for class jdistlib.inference.AcceleratedLogisticRegression
acceleration(double, double[], double[], double[], double[], double[]) - Method in interface jdistlib.inference.solver.HolonomicDaeSystem: Writes unconstrained acceleration into acceleration.
accept(int, double[], double, IterationStats) - Method in class jdistlib.inference.ChunkedDrawSink
accept(int, double[], double, IterationStats) - Method in interface jdistlib.inference.DrawSink
accept(int, double[], double, IterationStats) - Method in class jdistlib.inference.GeneratedQuantitySink
accept(int, double[], double, IterationStats) - Method in class jdistlib.inference.MappedDrawStore
accept(int, ReversibleJumpState, double, ReversibleJumpIterationStats) - Method in interface jdistlib.inference.ReversibleJumpDrawSink
accept(long, SparseSubsetState, double, SparseSubsetIterationStats) - Method in interface jdistlib.inference.SparseSubsetDrawSink
acceptanceProbabilities() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
acceptanceProbability() - Method in class jdistlib.inference.HybridKernelTransition
acceptanceProbability() - Method in class jdistlib.inference.IterationStats
acceptanceProbability() - Method in class jdistlib.inference.ReversibleJumpWithinModelTransition
acceptanceRate(int) - Method in class jdistlib.inference.HybridSamplerDiagnostics
accepted() - Method in class jdistlib.inference.ColumnarDraws
accepted() - Method in class jdistlib.inference.HybridKernelTransition
accepted() - Method in class jdistlib.inference.IterationStats
accepted() - Method in class jdistlib.inference.ReversibleJumpWithinModelTransition
acceptedSwaps() - Method in class jdistlib.inference.ParallelTemperingResult
accepts(int) - Method in class jdistlib.inference.HybridSamplerDiagnostics
active(int) - Method in class jdistlib.inference.SparseSubsetState
active(long, int) - Method in class jdistlib.inference.SubsetSelectionTarget
activeCandidate(int) - Method in class jdistlib.inference.SparseSubsetState
activeCandidates() - Method in class jdistlib.inference.SparseSubsetState
activeCandidates(long) - Method in class jdistlib.inference.SubsetSelectionTarget
activeIndex(int) - Method in class jdistlib.inference.SparseSubsetState
adaptationState() - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
adaptationState() - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
adaptationState() - Method in class jdistlib.inference.ModelSpecificRjKernel
adaptationState() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
adaptationState() - Method in interface jdistlib.inference.ReversibleJumpMove
adaptationState() - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
adaptationState() - Method in interface jdistlib.inference.RjBirthProposal
adaptationState() - Method in class jdistlib.inference.SubsetBirthMove
adaptationState() - Method in class jdistlib.inference.SubsetDeathMove
adaptationState() - Method in class jdistlib.inference.SubsetSwapMove
ADAPTIVE_LOG_CONCAVE_REJECTION - Enum constant in enum class jdistlib.SamplingStrategy
AdaptiveGaussianRjBirthProposal - Class in jdistlib.inference: Warmup-only candidate-specific Gaussian birth adaptation with checkpointable moments.
AdaptiveGaussianRjBirthProposal(int, double, double, double) - Constructor for class jdistlib.inference.AdaptiveGaussianRjBirthProposal
adaptiveProbeRounds(int) - Method in class jdistlib.FunctionAnalysisOptions.Builder
AdaptiveRejectionGibbsKernel - Class in jdistlib.inference: Rebuilds and draws a caller-certified log-concave full conditional.
AdaptiveRejectionGibbsKernel(int, AdaptiveRejectionGibbsKernel.ConditionalFactory) - Constructor for class jdistlib.inference.AdaptiveRejectionGibbsKernel
AdaptiveRejectionGibbsKernel.ConditionalFactory - Interface in jdistlib.inference
adaptiveRejectionLimits(int, int) - Method in class jdistlib.NumericalContinuousDistribution.Builder
AdaptiveRejectionSampler - Class in jdistlib: Adaptive tangent-envelope rejection sampler for a caller-certified differentiable log-concave density on finite support.
AdaptiveRejectionSampler(NumericalContinuousDistribution, UnivariateFunction, int, int, double...) - Constructor for class jdistlib.AdaptiveRejectionSampler
adaptiveRejectionSampling(UnivariateFunction, double...) - Method in class jdistlib.NumericalContinuousDistribution.Builder
AdaptiveRjRandomWalkKernel - Class in jdistlib.inference: Per-model isotropic random walk with warmup-only Robbins-Monro scale adaptation.
AdaptiveRjRandomWalkKernel(String, double, double) - Constructor for class jdistlib.inference.AdaptiveRjRandomWalkKernel
AdaptiveStaticHamiltonianMonteCarlo - Class in jdistlib.inference: Coordinated many-chain static HMC with ChEES or SNAPER trajectory adaptation.
AdaptiveStaticHmcOptions - Class in jdistlib.inference: Controls coordinated ChEES/SNAPER trajectory-length adaptation across chains.
AdaptiveStaticHmcOptions.Builder - Class in jdistlib.inference
AdaptiveStaticHmcOptions.Criterion - Enum Class in jdistlib.inference
AdaptiveStaticHmcResult - Class in jdistlib.inference: Draws plus the shared trajectory adaptation selected by ChEES or SNAPER.
adaptMassMatrix() - Method in class jdistlib.inference.SamplingOptions
adaptMassMatrix(boolean) - Method in class jdistlib.inference.SamplingOptions.Builder
adaptMoveWeights() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
adaptMoveWeights() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
adaptMoveWeights(boolean) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
adaptMoveWeights(boolean) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
adaptStepSize() - Method in class jdistlib.inference.SamplingOptions
adaptStepSize(boolean) - Method in class jdistlib.inference.SamplingOptions.Builder
add(int, double) - Method in class jdistlib.inference.autodiff.ReverseTape
add(int, int) - Method in class jdistlib.inference.autodiff.ReverseTape
add(Complex) - Method in class jdistlib.math.Complex
addGradient(String, int, double, double[]) - Method in class jdistlib.inference.ModelState
adjoint(int) - Method in class jdistlib.inference.autodiff.ReverseTape
adjust(double[], MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Adjusts p-values, counting only non-missing inputs as tests.
adjust(double[], MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Adjusts p-values for a declared total number of comparisons.
AdjustedMclmcTuner - Class in jdistlib.inference: Automatic adjusted-MCLMC pilot search for integrator step and decorrelation length.
AdjustedMclmcTuningOptions - Class in jdistlib.inference: Pilot-search controls for adjusted MCLMC step size and decorrelation length.
AdjustedMclmcTuningOptions.Builder - Class in jdistlib.inference
AdjustedMclmcTuningResult - Class in jdistlib.inference: Final adjusted-MCLMC chain and auditable pilot objective values.
AdjustedMicrocanonicalLangevin - Class in jdistlib.inference: Metropolis-adjusted microcanonical Langevin sampler (MHMCHMC).
AdjustedMicrocanonicalLangevin() - Constructor for class jdistlib.inference.AdjustedMicrocanonicalLangevin
adjustLog(double[], MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Adjusts natural-log p-values without exponentiating them.
adjustLog(double[], MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Adjusts natural-log p-values for a declared total family size.
adjustLogWeightedBenjaminiHochberg(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes weighted BH adjusted values directly from natural-log p-values.
adjustLogWeightedBenjaminiYekutieli(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Weighted BY adjustment for natural-log p-values.
adjustLogWeightedBonferroni(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Weighted Bonferroni adjustment for natural-log p-values.
adjustLogWeightedHolm(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Weighted Holm adjustment for natural-log p-values.
adjustWeightedBenjaminiHochberg(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes weighted Benjamini-Hochberg adjusted p-values.
adjustWeightedBenjaminiYekutieli(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes weighted Benjamini-Yekutieli adjusted p-values.
adjustWeightedBonferroni(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes weighted Bonferroni adjusted p-values.
adjustWeightedHolm(double[], double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes weighted Holm adjusted p-values.
AdvancedRiskMeasures - Class in jdistlib.finance: Spectral, distortion/Choquet, and entropic risk measures.
AdvancedRiskMeasures.Distortion - Interface in jdistlib.finance
AdvancedRiskMeasures.SpectralWeight - Interface in jdistlib.finance
affine(GenericDistribution, double, double) - Static method in class jdistlib.Distributions
affine(GenericDistribution, double, double) - Static method in class jdistlib.MonotoneTransformDistribution: Creates the distribution of shift + scale * X.
afterFinitePrefix(long, DiscreteTailBound) - Static method in class jdistlib.DiscreteTailBounds: Activates a remainder certificate only after a caller-verified finite prefix has been included.
aic() - Method in class jdistlib.CopulaFitResult
aic() - Method in class jdistlib.VineFitResult
AIC - Enum constant in enum class jdistlib.CopulaSelectionCriterion
algdiv(double, double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- COMPUTATION OF LN(GAMMA(B)/GAMMA(A+B)) WHEN B >= 8.
AlgebraicSolver - Class in jdistlib.inference.solver: Finite-difference Newton solver for small and medium dense algebraic systems.
AlgebraicSolver.Options - Class in jdistlib.inference.solver: Solver controls.
AlgebraicSolver.Result - Class in jdistlib.inference.solver: Converged root and diagnostic counts.
AlgebraicSystem - Interface in jdistlib.inference.solver: Residual function F(state, parameters, data) = 0.
allEq(double[], double) - Static method in class jdistlib.math.VectorMath
allEqual(double[], double[]) - Static method in class jdistlib.math.VectorMath
allEqual(double[], double[], double) - Static method in class jdistlib.math.VectorMath
allEqualScaled(double[], double[], double) - Static method in class jdistlib.math.VectorMath
allFinite(double[]) - Static method in class jdistlib.math.VectorMath
allGt(double[], double) - Static method in class jdistlib.math.VectorMath
allLt(double[], double) - Static method in class jdistlib.math.VectorMath
allowFiniteDifferences() - Method in class jdistlib.inference.SamplingOptions
allowFiniteDifferences(boolean) - Method in class jdistlib.inference.SamplingOptions.Builder
allReal() - Static method in class jdistlib.finance.TransformDomain
allVariables() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Result
alnrel(double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- Evaluation of the function ln(1 + a) -----------------------------------------------------------------------
analysisOptions(FunctionAnalysisOptions) - Method in class jdistlib.NumericalContinuousDistribution.Builder
analyze(String[], double[][], double, double) - Static method in class jdistlib.inference.ShrinkageSelection
analyze(String[], ChainResult...) - Static method in class jdistlib.inference.McmcDiagnostics
analyze(ChainResult...) - Static method in class jdistlib.inference.GeometryAdvisor
analyze(ChainResult...) - Static method in class jdistlib.inference.McmcDiagnostics
analyze(ReversibleJumpTarget, ReversibleJumpResult...) - Static method in class jdistlib.inference.ReversibleJumpDiagnostics
analyze(UnivariateFunction, double, double) - Static method in class jdistlib.NumericalContinuousDistribution: Analyzes a kernel and attempts construction using the analyzer's integration settings plus any suggested breakpoints.
analyze(UnivariateFunction, double, double) - Static method in class jdistlib.ProbabilityFunctionAnalyzer
analyze(UnivariateFunction, double, double, ConstructionPolicy) - Static method in class jdistlib.NumericalContinuousDistribution: Analyzes using defaults and an explicit construction policy.
analyze(UnivariateFunction, double, double, FunctionAnalysisOptions) - Static method in class jdistlib.NumericalContinuousDistribution: Analyzes and attempts construction with explicit analysis settings.
analyze(UnivariateFunction, double, double, FunctionAnalysisOptions) - Static method in class jdistlib.ProbabilityFunctionAnalyzer
analyze(NumericalContinuousDistribution) - Static method in class jdistlib.NumericalDistributionAnalyzer
analyze(NumericalContinuousDistribution, MomentAnalysisOptions) - Static method in class jdistlib.NumericalDistributionAnalyzer: Analyzes a continuous distribution with user-selected absolute moments.
analyze(NumericalDiscreteDistribution) - Static method in class jdistlib.NumericalDistributionAnalyzer
analyze(NumericalDiscreteDistribution, MomentAnalysisOptions) - Static method in class jdistlib.NumericalDistributionAnalyzer: Analyzes a finite discrete distribution with selected moment orders.
analyzeDistribution() - Method in class jdistlib.NumericalContinuousDistribution: Runs CDF, quantile, tail, normalization, and moment diagnostics.
analyzeDistribution() - Method in class jdistlib.NumericalDiscreteDistribution: Runs mass, CDF, quantile, tail, and moment diagnostics.
analyzeDistribution(MomentAnalysisOptions) - Method in class jdistlib.NumericalContinuousDistribution: Runs diagnostics with user-selected absolute-moment orders and tail split.
analyzeDistribution(MomentAnalysisOptions) - Method in class jdistlib.NumericalDiscreteDistribution: Runs diagnostics with user-selected absolute-moment orders and tail split.
analyzeLogKernel(UnivariateFunction, double, double) - Static method in class jdistlib.NumericalContinuousDistribution: Analyzes a log-kernel in log space and attempts construction using the default settings.
analyzeLogKernel(UnivariateFunction, double, double) - Static method in class jdistlib.ProbabilityFunctionAnalyzer: Analyzes a log-kernel without exponentiating its probe values.
analyzeLogKernel(UnivariateFunction, double, double, ConstructionPolicy) - Static method in class jdistlib.NumericalContinuousDistribution: Analyzes a log-kernel with defaults and an explicit policy.
analyzeLogKernel(UnivariateFunction, double, double, FunctionAnalysisOptions) - Static method in class jdistlib.NumericalContinuousDistribution: Analyzes and attempts log-kernel construction with explicit settings.
analyzeLogKernel(UnivariateFunction, double, double, FunctionAnalysisOptions) - Static method in class jdistlib.ProbabilityFunctionAnalyzer: Analyzes a log-kernel with explicit settings.
anderson_darling_pvalue(double, int) - Static method in class jdistlib.disttest.NormalityTest
anderson_darling_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest
anderson_darling_statistic(double[], GenericDistribution) - Static method in class jdistlib.disttest.DistributionTest: One-sample Anderson-Darling statistic against a fully specified continuous reference distribution.
anderson_darling_test(double[], GenericDistribution) - Static method in class jdistlib.disttest.DistributionTest: One-sample Anderson-Darling test using a deterministic parametric bootstrap.
anderson_darling_test(double[], GenericDistribution, int, RandomEngine) - Static method in class jdistlib.disttest.DistributionTest: One-sample Anderson-Darling test with caller-controlled bootstrap sampling.
Ansari - Class in jdistlib: Ansari-Bradley test statistic
Ansari(int, int) - Constructor for class jdistlib.Ansari
ansari_bradley_test(double[], double[], boolean) - Static method in class jdistlib.disttest.DistributionTest: Return the two-sided test of Ansari-Bradley.
ansari_bradley_test(double[], double[], boolean, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Ansari-Bradley test.
any(boolean...) - Static method in class jdistlib.util.Utilities
anyNA(double...) - Static method in class jdistlib.util.Utilities
api() - Method in class jdistlib.accelerator.ComputeDeviceInfo
apiVersion() - Method in class jdistlib.accelerator.ComputeDeviceInfo
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in class jdistlib.inference.FixedDimensionSamplerRjKernel
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in class jdistlib.inference.ModelSpecificRjKernel
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in interface jdistlib.inference.ReversibleJumpMove
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in class jdistlib.inference.SubsetBirthMove
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in class jdistlib.inference.SubsetDeathMove
applicable(ReversibleJumpState, ReversibleJumpTarget) - Method in class jdistlib.inference.SubsetSwapMove
apply(double) - Method in interface jdistlib.finance.DistributionAggregation.ScenarioTransformation
apply(SamplingOptions, String, String, boolean) - Method in class jdistlib.inference.WarmupBundle
applyTo(SamplingOptions.Builder) - Method in class jdistlib.inference.InferenceCliOptions: Applies parsed compute switches without replacing other builder settings.
ApproximationFunction - Class in jdistlib.math.approx: Create an approximation function.
ApproximationFunction(ApproximationType, double[], double[], double, double, double) - Constructor for class jdistlib.math.approx.ApproximationFunction
ApproximationType - Enum Class in jdistlib.math.approx: Types of approximation
apser(double, double, double, double) - Static method in class jdistlib.math.MathFunctions
architecture() - Method in class jdistlib.accelerator.ComputeDeviceInfo
Arcsine - Class in jdistlib: Bounded Arcsine distribution; bounded by [a, b].
Arcsine(double, double) - Constructor for class jdistlib.Arcsine
areDecisionsExact() - Method in class jdistlib.disttest.MultipleTesting.CensoredTestResult: Returns whether the censoring limit rules out every unrecorded hypothesis from rejection at the requested level.
areMomentsStable() - Method in class jdistlib.DistributionAnalysis
arg() - Method in class jdistlib.math.Complex
as_numeric(Collection<String>) - Static method in class jdistlib.math.VectorMath
asMap() - Method in class jdistlib.inference.ModelData
assess(Copula, double[][]) - Static method in class jdistlib.CopulaLikelihoodDiagnostics: Evaluates every row without modifying the supplied observations.
assess(McmcDiagnosticReport) - Static method in class jdistlib.inference.InferenceHealth
assess(McmcDiagnosticReport, PathfinderFit, GradientCheckResult) - Static method in class jdistlib.inference.InferenceHealth
assessStability(UnivariateFunction, double, double, IntegrationOptions) - Static method in class jdistlib.math.Integrate: Repeats an integral with tighter tolerances and an additional midpoint split.
ASUM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
AsymmetricLaplace - Class in jdistlib: Three-parameter asymmetric Laplace distribution used in quantile regression.
AsymmetricLaplace(double, double, double) - Constructor for class jdistlib.AsymmetricLaplace
atom(double) - Method in class jdistlib.NumericalSupport.Builder
AtomAwareDistribution - Interface in jdistlib: A scalar distribution that can report probability mass at an exact point.
atomic(double, int[], double[]) - Method in class jdistlib.inference.autodiff.ReverseTape: Creates an allocation-free many-input atomic node.
atomProbability(double) - Method in interface jdistlib.AtomAwareDistribution: Returns P(X = x); zero means no declared atom at x.
atomProbability(double) - Method in class jdistlib.CensoredDistribution
atomProbability(double) - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
atomProbability(double) - Method in class jdistlib.finance.DelaporteDistribution
atomProbability(double) - Method in class jdistlib.finance.EmpiricalDistribution
atomProbability(double) - Method in class jdistlib.finance.FiniteGridDistribution
atomProbability(double) - Method in class jdistlib.finance.OptionImpliedDistribution
atomProbability(double) - Method in class jdistlib.finance.PolyaAeppliDistribution
atomProbability(double) - Method in class jdistlib.MixtureDistribution
atomProbability(double) - Method in class jdistlib.MonotoneTransformDistribution
atomProbability(double) - Method in class jdistlib.NumericalDiscreteDistribution
atomProbability(double) - Method in class jdistlib.NumericalPiecewiseDistribution
atomProbability(double) - Method in class jdistlib.PhaseType
atomWeights(UnivariateFunction) - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
attemptedSwaps() - Method in class jdistlib.inference.ParallelTemperingResult
attempts(int) - Method in class jdistlib.inference.HybridSamplerDiagnostics
AUTO - Enum constant in enum class jdistlib.accelerator.Compute: Route eligible large operations to an available accelerator and small work to CPU.
AUTO - Enum constant in enum class jdistlib.inference.ComputeNuts: Use the configured compute policy and its profitability thresholds.
AUTO - Enum constant in enum class jdistlib.math.IntegrationOptions.Method: QUADPACK with CQUAD and double-exponential fallbacks.
autocorrelation(String, int, int, ChainResult...) - Static method in class jdistlib.inference.DiagnosticGraphs
AUTOMATIC - Enum constant in enum class jdistlib.accelerator.ComputeApi
AUTOMATIC - Enum constant in enum class jdistlib.accelerator.ExecutionKind
automaticRouting() - Method in interface jdistlib.accelerator.ComputeBackend: Whether individual operations may route between CPU and the selected provider.
automaticRouting() - Method in class jdistlib.accelerator.ComputeSelection
auxiliary() - Method in class jdistlib.inference.DimensionMatchingResult
available() - Method in interface jdistlib.accelerator.ComputeBackend
available() - Static method in class jdistlib.accelerator.ComputeBackends
available() - Method in class jdistlib.accelerator.CpuComputeBackend
AVERAGE - Enum constant in enum class jdistlib.util.Utilities.RankTies
axpy(double, double[], double[]) - Method in interface jdistlib.accelerator.ComputeBackend
axpy(double, double[], double[]) - Method in class jdistlib.accelerator.CpuComputeBackend
AXPY - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation

B

b - Variable in class jdistlib.Arcsine
b - Variable in class jdistlib.Beta
b - Variable in class jdistlib.HyperGeometric
b - Variable in class jdistlib.Kumaraswamy
b - Variable in class jdistlib.NonCentralBeta
b - Variable in class jdistlib.Uniform
bachelier(double, double, double, double, double, boolean) - Static method in class jdistlib.finance.ReferenceOptions
backend() - Method in class jdistlib.accelerator.ComputeCapabilities
backend() - Method in class jdistlib.accelerator.ComputeSelection: Returns the owned backend; closing this selection closes it.
backend() - Method in class jdistlib.inference.AcceleratedLogisticRegression
backend(Compute) - Method in class jdistlib.inference.SamplingOptions.Builder: Short alias for SamplingOptions.Builder.computeBackend(Compute).
backendId() - Method in class jdistlib.accelerator.ComputeDeviceInfo
backendId() - Method in class jdistlib.accelerator.ExecutionPlan
backendVersion() - Method in class jdistlib.accelerator.ComputeDeviceInfo
BAD_INTEGRAND_BEHAVIOUR - Enum constant in enum class jdistlib.math.IntegrationStatus
Bandwidth - Class in jdistlib.math.density
Bandwidth() - Constructor for class jdistlib.math.density.Bandwidth
BAR - Enum constant in enum class jdistlib.inference.ChartSpec.Type
BarkerGradientSampler - Class in jdistlib.inference: Exact gradient-informed Barker proposal with symmetric Gaussian magnitudes.
BarkerGradientSampler() - Constructor for class jdistlib.inference.BarkerGradientSampler
bartlett_test(double[], int[]) - Static method in class jdistlib.disttest.DistributionTest: Bartlett's test
baseLogDensity(double[]) - Method in interface jdistlib.inference.TemperedLogDensity
basym(double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions
BATCHED_GEMM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
BATCHED_GETRF - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
BATCHED_POTRF - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
BatchedDifferentiableLogDensity - Interface in jdistlib.inference: Optional accelerator-facing contract for evaluating independent states in one call.
batchedLinearAlgebra() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether the provider accepts batched dense operations through the public contract.
BayesianModel - Class in jdistlib.inference: Compiled named model evaluated on an unconstrained state space.
BB1 - Enum constant in enum class jdistlib.CopulaFamily
BB1Copula - Class in jdistlib: Bivariate BB1 (Clayton-Gumbel) copula, theta >= 0 and delta >= 1.
BB1Copula(double, double) - Constructor for class jdistlib.BB1Copula
bcorr(double, double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF DEL(A0) + DEL(B0) - DEL(A0 + B0) WHERE LN(GAMMA(A)) = (A - 0.5)*LN(A) - A + 0.5*LN(2*PI) + DEL(A).
BCV - Static variable in class jdistlib.math.density.Bandwidth
bd - Variable in class jdistlib.BetaBinomial
bd0(double, double) - Static method in class jdistlib.math.MathFunctions
beforeFinitePrefix(long, DiscreteTailBound) - Static method in class jdistlib.DiscreteTailBounds: Left-moving counterpart of DiscreteTailBounds.afterFinitePrefix(long, DiscreteTailBound).
BENJAMINI_HOCHBERG - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Benjamini-Hochberg false-discovery-rate control.
BENJAMINI_YEKUTIELI - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Benjamini-Yekutieli FDR control under arbitrary dependence.
benjaminiKriegerYekutieli(double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Runs the Benjamini-Krieger-Yekutieli two-stage linear step-up test.
benjaminiKriegerYekutieli(double[], double, int) - Static method in class jdistlib.disttest.MultipleTesting: Runs two-stage BKY for a declared total family size.
Bessel - Class in jdistlib.math: Collection of Bessel functions.
Bessel() - Constructor for class jdistlib.math.Bessel
beta(double, double) - Static method in class jdistlib.math.MathFunctions: This function returns the value of the beta function evaluated with arguments a and b.
Beta - Class in jdistlib
Beta(double, double) - Constructor for class jdistlib.Beta
BetaBinomial - Class in jdistlib: Beta binomial distribution, taken from gamlss.dist package, plus some underflow guard.
BetaBinomial(double, double, int) - Constructor for class jdistlib.BetaBinomial
betaln(double, double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- Evaluation of the logarithm of the beta function ln(beta(a0,b0)) -----------------------------------------------------------------------
BetaNegativeBinomial - Class in jdistlib: Beta-negative-binomial distribution using the extraDistr parameterization.
BetaNegativeBinomial(double, double, double) - Constructor for class jdistlib.BetaNegativeBinomial
BetaPrime - Class in jdistlib: Beta-prime (beta of the second kind) distribution.
BetaPrime(double, double) - Constructor for class jdistlib.BetaPrime
betaPrior(String, double, double) - Static method in class jdistlib.inference.ModelFactors
bfrac(double, double, double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions
bgrat(double, double, double, double, double, double, int[], boolean) - Static method in class jdistlib.math.MathFunctions
bic() - Method in class jdistlib.CopulaFitResult
bic() - Method in class jdistlib.VineFitResult
BIC - Enum constant in enum class jdistlib.CopulaSelectionCriterion
bigx - Static variable in class jdistlib.math.MathFunctions
binary() - Static method in class jdistlib.inference.CoordinateSupport
bind(String, StanExternalFunction) - Method in class jdistlib.inference.lang.ExternalFunctionRegistry.Builder
Binomial - Class in jdistlib
Binomial(double, double) - Constructor for class jdistlib.Binomial
Binomial(double, double, Binomial.BinomialKind) - Constructor for class jdistlib.Binomial
binomial_test(int, int, double, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Binomial test
Binomial.BinomialKind - Enum Class in jdistlib: Selects the BTPE acceptance test used for binomial random generation.
Binomial.RandomState - Class in jdistlib
binomialObservation(String, String, String) - Static method in class jdistlib.inference.ModelFactors
BirnbaumSaunders - Class in jdistlib: Birnbaum-Saunders (fatigue-life) distribution with shape alpha, scale beta, and location mu.
BirnbaumSaunders(double, double, double) - Constructor for class jdistlib.BirnbaumSaunders
BivariateLogistic - Class in jdistlib: Gumbel's type-I bivariate logistic distribution as used by VGAM.
BivariatePoisson - Class in jdistlib: Bivariate Poisson distribution formed from three independent Poisson counts.
BIWEIGHT - Enum constant in enum class jdistlib.math.density.Kernel
blackScholes(double, double, double, double, double, boolean) - Static method in class jdistlib.finance.ReferenceOptions
BLOCK_DIAGONAL - Enum constant in enum class jdistlib.inference.MetricConfiguration.Type
blockDiagonal(int[]...) - Static method in class jdistlib.inference.MetricConfiguration
blocks() - Method in class jdistlib.inference.MetricConfiguration
blockSizes() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
blockSizes() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
bobyqa(double[], double[], double[], MultivariableFunction, int, double, double, int, boolean) - Static method in class jdistlib.math.opt.Bobyqa: This subroutine seeks the least value of a function of many variables, by applying a trust region method that forms quadratic models by interpolation.
Bobyqa - Class in jdistlib.math.opt: Translation of the infamous Bobyqa algorithm by Michael J.
Bobyqa() - Constructor for class jdistlib.math.opt.Bobyqa
BobyqaConfig - Class in jdistlib.math.opt
BobyqaConfig() - Constructor for class jdistlib.math.opt.BobyqaConfig
BobyqaConfig(double[], double[], double[], MultivariableFunction) - Constructor for class jdistlib.math.opt.BobyqaConfig
BobyqaConfig(double[], double[], double[], MultivariableFunction, int, boolean) - Constructor for class jdistlib.math.opt.BobyqaConfig
BobyqaConfig(double[], double[], double[], MultivariableFunction, int, boolean, double, double, int) - Constructor for class jdistlib.math.opt.BobyqaConfig
BobyqaConfig(OptimizationConfig) - Constructor for class jdistlib.math.opt.BobyqaConfig
BONFERRONI - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Bonferroni family-wise error-rate control.
Bool3 - Enum Class in jdistlib.util: Three-state boolean: TRUE, FALSE, NA
bootstrapReturnLevel(double[], double, int, long) - Static method in class jdistlib.finance.ExtremeValueInference
BOUNDARY - Enum constant in enum class jdistlib.CopulaDiagnostics.Classification
boundaryProbability(double, double, double) - Static method in class jdistlib.Wiener: Boundary-choice probability, equal to the integral of Wiener.density(double, double, double, double, double, boolean).
bounded(double, double) - Static method in class jdistlib.inference.Constraints
BOUNDED_REAL - Enum constant in enum class jdistlib.inference.CoordinateSupport.Kind
boundedReal(double, double) - Static method in class jdistlib.inference.CoordinateSupport
boundedVector(double, double, int) - Static method in class jdistlib.inference.Constraints
bpser(double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions
bratio(double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- Evaluation of the Incomplete Beta function I_x(a,b) -------------------- It is assumed that a and b are nonnegative, and that x <= 1 and y = 1 - x.
brcmp1(int, double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions
brcomp(double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions
breakpoints(double...) - Method in class jdistlib.math.IntegrationOptions.Builder: Declares finite locations at which the interval should be split.
BTPE - Enum constant in enum class jdistlib.Binomial.BinomialKind
BUGGY_BTPE - Enum constant in enum class jdistlib.Binomial.BinomialKind
build() - Method in class jdistlib.CdfTableOptions.Builder
build() - Method in class jdistlib.CertifiedDiscreteOptions.Builder
build() - Method in class jdistlib.FunctionAnalysisOptions.Builder
build() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
build() - Method in class jdistlib.inference.AdjustedMclmcTuningOptions.Builder
build() - Method in class jdistlib.inference.lang.ExternalFunctionRegistry.Builder
build() - Method in class jdistlib.inference.ModelBuilder
build() - Method in class jdistlib.inference.PathfinderOptions.Builder
build() - Method in class jdistlib.inference.PrecisionGoal.Builder
build() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
build() - Method in class jdistlib.inference.SamplingOptions.Builder
build() - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
build() - Method in class jdistlib.math.IntegrationOptions.Builder
build() - Method in class jdistlib.MomentAnalysisOptions.Builder
build() - Method in class jdistlib.NumericalContinuousDistribution.Builder
build() - Method in class jdistlib.NumericalDiscreteDistribution.Builder
build() - Method in class jdistlib.NumericalDistributionBuildResult: Returns the constructed distribution or throws with the retained cause.
build() - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
build() - Method in class jdistlib.NumericalSupport.Builder
build(double, double, double, OptionObservation...) - Static method in class jdistlib.finance.OptionCurve
builder() - Static method in class jdistlib.CdfTableOptions
builder() - Static method in class jdistlib.CertifiedDiscreteOptions
builder() - Static method in class jdistlib.FunctionAnalysisOptions
builder() - Static method in class jdistlib.inference.AdaptiveStaticHmcOptions
builder() - Static method in class jdistlib.inference.AdjustedMclmcTuningOptions
builder() - Static method in class jdistlib.inference.lang.ExternalFunctionRegistry
builder() - Static method in class jdistlib.inference.PathfinderOptions
builder() - Static method in class jdistlib.inference.ReversibleJumpSamplingOptions
builder() - Static method in class jdistlib.inference.SamplingOptions
builder() - Static method in class jdistlib.inference.SparseSubsetSamplingOptions
builder() - Static method in class jdistlib.math.IntegrationOptions: Returns a builder initialized to R-compatible integration defaults.
builder() - Static method in class jdistlib.MomentAnalysisOptions
builder() - Static method in class jdistlib.NumericalContinuousDistribution: Returns a fluent builder for a custom continuous distribution.
builder() - Static method in class jdistlib.NumericalDiscreteDistribution: Returns a fluent builder for a finite custom discrete distribution.
builder() - Static method in class jdistlib.NumericalPiecewiseDistribution: Returns a fluent builder for interval unions with optional atoms.
builder() - Static method in class jdistlib.NumericalSupport
builder(int) - Static method in class jdistlib.inference.PrecisionGoal
builder(ToDoubleFunction<double[]>) - Static method in class jdistlib.inference.PrecisionGoal
Builder() - Constructor for class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
Builder() - Constructor for class jdistlib.inference.AdjustedMclmcTuningOptions.Builder
Builder() - Constructor for class jdistlib.inference.lang.ExternalFunctionRegistry.Builder
Builder() - Constructor for class jdistlib.inference.PathfinderOptions.Builder
bulkEffectiveSampleSize() - Method in class jdistlib.inference.ParameterDiagnostics
bup(double, double, double, double, int, double, boolean) - Static method in class jdistlib.math.MathFunctions
byId(String) - Static method in class jdistlib.accelerator.ComputeBackends

C

c - Variable in class jdistlib.Binomial.RandomState
c(double...) - Static method in class jdistlib.util.Utilities
c(double[]...) - Static method in class jdistlib.util.Utilities
c(int...) - Static method in class jdistlib.util.Utilities
c(int[]...) - Static method in class jdistlib.util.Utilities
C_VINE - Enum constant in enum class jdistlib.VineStructure
calculate(double[]) - Method in class jdistlib.math.density.Bandwidth
calculate_count(double, int) - Static method in class jdistlib.Kendall
calculate_ecdf(double[]) - Static method in class jdistlib.disttest.Utils: Calculate the CDF of empirical distribution
calculate_ncp(double, double, double, double) - Static method in class jdistlib.NonCentralBeta: Given prob, x, a and b, this function returns the corresponding noncentrality parameter of the noncentral beta distribution.
calculate_tau(double, int) - Static method in class jdistlib.Kendall
calculateXtY(double[][], double[][]) - Static method in class jdistlib.matrix.QMatrixUtils: Deprecated.

Calculate X'Y.
calculateXY(double[][], double[][]) - Static method in class jdistlib.matrix.QMatrixUtils: Deprecated.

Calculate XY.
calculateXYt(double[][], double[][]) - Static method in class jdistlib.matrix.QMatrixUtils: Deprecated.

Calculate XY'.
CALLBACK_FAILED - Enum constant in enum class jdistlib.math.IntegrationStatus
CALLBACK_TIME_LIMIT_EXCEEDED - Enum constant in enum class jdistlib.math.IntegrationStatus
callbackExecution(IntegrationOptions.CallbackExecution) - Method in class jdistlib.math.IntegrationOptions.Builder: Selects direct or opt-in private-daemon callback execution.
callbackProfile - Variable in class jdistlib.math.IntegrationResult: Callback timing captured by the hardened API.
CallbackProfile - Class in jdistlib.math: Immutable wall-clock cost profile for integrand callback evaluations.
CALLER_THREAD - Enum constant in enum class jdistlib.math.IntegrationOptions.CallbackExecution: Evaluate on the integrating thread with no worker overhead.
callPayoff(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk
calls() - Method in class jdistlib.inference.FactorProfile
canBuild() - Method in class jdistlib.NumericalDistributionBuildResult
cancellation(BooleanSupplier) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
cancellation(BooleanSupplier) - Method in class jdistlib.inference.SamplingOptions.Builder
cancellation(BooleanSupplier) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
cancellation(BooleanSupplier) - Method in class jdistlib.math.IntegrationOptions.Builder
cancelled() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
cancelled() - Method in class jdistlib.inference.SamplingOptions
CANCELLED - Enum constant in enum class jdistlib.inference.ChainResult.Status
CANCELLED - Enum constant in enum class jdistlib.inference.ReversibleJumpResult.Status
CANCELLED - Enum constant in enum class jdistlib.inference.SparseSubsetResult.Status
CANCELLED - Enum constant in enum class jdistlib.math.IntegrationStatus
candidate() - Method in class jdistlib.inference.SparseCandidateChoice
candidateCount() - Method in class jdistlib.inference.SparseSubsetTarget
candidateCount() - Method in class jdistlib.inference.SubsetSelectionTarget
candidateName(int) - Method in class jdistlib.inference.SparseSubsetTarget
candidateName(int) - Method in class jdistlib.inference.SubsetSelectionTarget
candidateNames() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
candidateNames() - Method in class jdistlib.inference.SparseSubsetTarget
candidateNames() - Method in class jdistlib.inference.SubsetSelectionTarget
candidates() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
candidateScores() - Method in class jdistlib.inference.AdaptiveStaticHmcResult
capabilities() - Method in interface jdistlib.accelerator.ComputeBackend
capabilities() - Method in class jdistlib.accelerator.CpuComputeBackend
capacity() - Method in class jdistlib.inference.autodiff.ReverseTape: Current reusable arena capacity.
categorical(int) - Static method in class jdistlib.inference.CoordinateSupport
Categorical - Class in jdistlib: Finite categorical distribution over numeric outcomes.
Categorical(double[]) - Constructor for class jdistlib.Categorical
Categorical(double[], double[]) - Constructor for class jdistlib.Categorical
CATEGORICAL - Enum constant in enum class jdistlib.inference.CoordinateSupport.Kind
categoryCount() - Method in class jdistlib.inference.CoordinateSupport
Cauchy - Class in jdistlib
Cauchy() - Constructor for class jdistlib.Cauchy: Standard constructor for Cauchy (location = 0, scale = 1)
Cauchy(double, double) - Constructor for class jdistlib.Cauchy
cause - Variable in class jdistlib.math.IntegrationResult: Original callback failure, when one was caught by the hardened API.
cc - Variable in class jdistlib.Tukey
cdf(double) - Method in class jdistlib.disttest.DiscretePValueDistribution: Evaluates the right-continuous CDF.
cdfEvaluations - Variable in class jdistlib.CopulaMeasureResult
cdfTable(CdfTableOptions) - Method in class jdistlib.NumericalContinuousDistribution.Builder
CdfTableOptions - Class in jdistlib: Immutable settings for an adaptive monotone numerical CDF table.
CdfTableOptions.Builder - Class in jdistlib
censor(GenericDistribution, double, double) - Static method in class jdistlib.Distributions
CensoredDistribution - Class in jdistlib: Winsorized/censored scalar distribution with explicit atoms at both bounds.
CensoredDistribution(GenericDistribution, double, double) - Constructor for class jdistlib.CensoredDistribution
centralMoment(double) - Method in class jdistlib.NumericalContinuousDistribution: Numerically evaluates E[(X-E[X])^order].
centralMoment(double) - Method in class jdistlib.NumericalDiscreteDistribution
CERTIFIED_REJECTION - Enum constant in enum class jdistlib.SamplingStrategy
CertifiedDiscreteOptions - Class in jdistlib: Immutable truncation settings for certified infinite discrete supports.
CertifiedDiscreteOptions.Builder - Class in jdistlib
CertifiedInfiniteDiscreteDistribution - Class in jdistlib: Finite approximation to an infinite integer-supported distribution, stopped only when user-provided tail certificates bound the omitted probability.
CgmyDistribution - Class in jdistlib.finance: CGMY/KoBoL infinitely-divisible return law in (C,G,M,Y,location) form.
CgmyDistribution(double, double, double, double, double) - Constructor for class jdistlib.finance.CgmyDistribution
CgmyDistribution(double, double, double, double, double, FourierInversionOptions) - Constructor for class jdistlib.finance.CgmyDistribution
chain() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
chain() - Method in class jdistlib.inference.HybridSamplingResult
chain() - Method in class jdistlib.inference.PrecisionContinuationResult
ChainCheckpoint - Class in jdistlib.inference: In-memory state-and-stream restart point including a cloned random engine.
ChainCheckpoint(double[], double, int, RandomEngine) - Constructor for class jdistlib.inference.ChainCheckpoint
ChainCheckpoint(double[], double, int, RandomEngine, SamplerCheckpoint) - Constructor for class jdistlib.inference.ChainCheckpoint
ChainExport - Class in jdistlib.inference: Versioned JSON and tidy CSV interchange for retained chain draws.
ChainResult - Class in jdistlib.inference: Immutable retained samples, sampler statistics, adaptation and restart state.
ChainResult(double[][], double[], IterationStats[], WarmupResult, ChainCheckpoint, ChainResult.Status, List<String>) - Constructor for class jdistlib.inference.ChainResult
ChainResult.Status - Enum Class in jdistlib.inference
chains() - Method in class jdistlib.inference.AdaptiveStaticHmcResult
chains() - Method in class jdistlib.inference.Fit
chains() - Method in class jdistlib.inference.ManyShortChainsResult
chains() - Method in class jdistlib.inference.McmcDiagnosticReport
chains() - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
Chains - Class in jdistlib.inference: Deterministic multi-chain execution and checkpoint continuation helpers.
chainsPerSuperchain() - Method in class jdistlib.inference.SuperchainPlan
chainStarts() - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
ChartSpec - Class in jdistlib.inference: Chart-neutral immutable dataset suitable for SVG, JSON, CSV, or UI adapters.
ChartSpec(String, String, String, ChartSpec.Type, List<ChartSpec.Series>) - Constructor for class jdistlib.inference.ChartSpec
ChartSpec.Series - Class in jdistlib.inference
ChartSpec.Type - Enum Class in jdistlib.inference
chebyshev_eval(double, double[], int) - Static method in class jdistlib.math.MathFunctions: evaluate the n-term Chebyshev series "a" at "x".
check(DifferentiableLogDensity, double[], double, double) - Static method in class jdistlib.inference.Gradients
checkpoint() - Method in class jdistlib.inference.ChainResult
checkpoint() - Method in class jdistlib.inference.PortableCheckpoint
checkpoint() - Method in class jdistlib.inference.PortableReversibleJumpCheckpoint
checkpoint() - Method in class jdistlib.inference.PortableSparseSubsetCheckpoint
checkpoint() - Method in class jdistlib.inference.ReversibleJumpResult
checkpoint() - Method in class jdistlib.inference.SparseSubsetResult
CheckpointIO - Class in jdistlib.inference: Checksummed, versioned binary checkpoint envelope with compatibility fingerprints.
CHEES - Enum constant in enum class jdistlib.inference.AdaptiveStaticHmcOptions.Criterion
Chi - Class in jdistlib
Chi(double) - Constructor for class jdistlib.Chi
chi_square_goodness_of_fit_test(long[], double[], int) - Static method in class jdistlib.disttest.DistributionTest: Pearson chi-square goodness-of-fit test for categorical counts.
chi_square_independence_test(long[][]) - Static method in class jdistlib.disttest.DistributionTest: Pearson chi-square test of independence for a contingency table.
ChiSquare - Class in jdistlib
ChiSquare(double) - Constructor for class jdistlib.ChiSquare
CholeskyFactor - Class in jdistlib.accelerator: Immutable lower Cholesky factor with reusable SPD solves.
CholeskyFactor(int, double[]) - Constructor for class jdistlib.accelerator.CholeskyFactor: Creates a factor from a row-major lower-triangular matrix.
choleskyFactorCorrelation(int) - Static method in class jdistlib.inference.Constraints: Stan-compatible Cholesky factor of a correlation matrix, stored row-major.
choleskyFactorCovariance(int, int) - Static method in class jdistlib.inference.Constraints: Stan-compatible lower Cholesky factor of an rows x columns covariance matrix.
choose(double, double) - Static method in class jdistlib.math.MathFunctions
chooseHigherDegreePolynomial(Polynomial, Polynomial) - Static method in class jdistlib.math.Polynomial
chooseLowerDegreePolynomial(Polynomial, Polynomial) - Static method in class jdistlib.math.Polynomial
ChunkedDrawSink - Class in jdistlib.inference: Selected-coordinate streaming sink with independently compressed, recoverable chunks.
ChunkedDrawSink(Path, int[], int) - Constructor for class jdistlib.inference.ChunkedDrawSink
chunks() - Method in class jdistlib.inference.PrecisionContinuationResult
CLAYTON - Enum constant in enum class jdistlib.CopulaFamily
ClaytonCopula - Class in jdistlib: Exchangeable Clayton copula with nonnegative dependence.
ClaytonCopula(int, double) - Constructor for class jdistlib.ClaytonCopula
clearAdaptiveRejectionSampling() - Method in class jdistlib.NumericalContinuousDistribution
clearCdfTable() - Method in class jdistlib.NumericalContinuousDistribution: Drops the table so the next CDF or central quantile call rebuilds it.
clearGaussian() - Method in class jdistlib.rng.MersenneTwister: Clears the internal gaussian variable from the RNG.
clearGaussian() - Method in class jdistlib.rng.MersenneTwisterSafe: Clears the internal gaussian variable from the RNG.
clearRejectionSampling() - Method in class jdistlib.NumericalContinuousDistribution: Restores inverse-CDF sampling.
CLOCKWISE_270 - Enum constant in enum class jdistlib.RotatedCopula.Rotation
CLOCKWISE_90 - Enum constant in enum class jdistlib.RotatedCopula.Rotation
clone() - Method in class jdistlib.math.Polynomial: Clone this polynomial
clone() - Method in class jdistlib.rng.MersenneTwister
clone() - Method in class jdistlib.rng.MersenneTwisterSafe
clone() - Method in class jdistlib.rng.RandomCMWC
clone() - Method in class jdistlib.rng.RandomEngine
clone() - Method in class jdistlib.rng.RandomWELL44497b
close() - Method in interface jdistlib.accelerator.ComputeBackend
close() - Method in class jdistlib.accelerator.ComputeSelection
close() - Method in class jdistlib.accelerator.CpuComputeBackend
close() - Method in interface jdistlib.accelerator.PreparedCholesky
close() - Method in interface jdistlib.accelerator.PreparedCsrMatrix
close() - Method in interface jdistlib.accelerator.PreparedDenseMatrix
close() - Method in interface jdistlib.accelerator.PreparedFloatCholesky
close() - Method in interface jdistlib.accelerator.PreparedFloatCsrMatrix
close() - Method in interface jdistlib.accelerator.PreparedFloatDenseMatrix
close() - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
close() - Method in interface jdistlib.accelerator.PreparedLogisticRegression
close() - Method in interface jdistlib.accelerator.PreparedSparseCholesky
close() - Method in interface jdistlib.accelerator.PreparedTransposeProduct
close() - Method in class jdistlib.inference.AcceleratedLogisticRegression
close() - Method in class jdistlib.inference.ChunkedDrawSink
close() - Method in class jdistlib.inference.lang.LoadedGeneratedModel
close() - Method in class jdistlib.inference.MappedDrawStore
close() - Method in class jdistlib.inference.ResidualInformedSparseCandidateProposal
close() - Method in interface jdistlib.inference.SparseCandidateProposal
code() - Method in class jdistlib.inference.HealthIssue
code() - Method in enum class jdistlib.MultivariateProbabilityStatus: Stable legacy integer code.
coefficient(int) - Method in class jdistlib.inference.SparseSubsetState
coefficientCounts() - Method in class jdistlib.inference.SparseSubsetCheckpoint
coefficients() - Method in class jdistlib.inference.SparseSubsetState
coefficientSquareSums() - Method in class jdistlib.inference.SparseSubsetCheckpoint
coefficientSums() - Method in class jdistlib.inference.SparseSubsetCheckpoint
coldChain() - Method in class jdistlib.inference.ParallelTemperingResult
colon(double, double) - Static method in class jdistlib.util.Utilities
colon(int, int) - Static method in class jdistlib.util.Utilities
column() - Method in class jdistlib.inference.lang.ScriptDiagnostic
column(int) - Method in class jdistlib.inference.ColumnarDraws
ColumnarDraws - Class in jdistlib.inference: Selected-coordinate columns read from a chunked draw store.
columnIndices() - Method in class jdistlib.matrix.CsrMatrix
columnIndices() - Method in class jdistlib.matrix.FloatCsrMatrix
columns() - Method in class jdistlib.accelerator.FloatPivotedQrFactor
columns() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition
columns() - Method in class jdistlib.accelerator.PivotedQrFactor: Returns the number of columns in the original matrix.
columns() - Method in interface jdistlib.accelerator.PreparedCsrMatrix
columns() - Method in interface jdistlib.accelerator.PreparedDenseMatrix
columns() - Method in interface jdistlib.accelerator.PreparedFloatCsrMatrix
columns() - Method in interface jdistlib.accelerator.PreparedFloatDenseMatrix
columns() - Method in interface jdistlib.accelerator.PreparedTransposeProduct
columns() - Method in class jdistlib.accelerator.SingularValueDecomposition
columns() - Method in class jdistlib.matrix.CsrMatrix
columns() - Method in class jdistlib.matrix.FloatCsrMatrix
combine(CallbackProfile...) - Static method in class jdistlib.math.CallbackProfile: Combines sequential profiles, saturating nanosecond totals on overflow.
commonDimension() - Method in class jdistlib.inference.SparseSubsetState
commonDimension() - Method in class jdistlib.inference.SparseSubsetTarget
commonDimension() - Method in class jdistlib.inference.SubsetSelectionTarget
commonMean(int) - Method in class jdistlib.inference.SparseSubsetSummary
commonParameter(int) - Method in class jdistlib.inference.SparseSubsetState
commonParameterName(int) - Method in class jdistlib.inference.SparseSubsetTarget
commonParameterNames() - Method in class jdistlib.inference.SparseSubsetTarget
commonParameterNames() - Method in class jdistlib.inference.SubsetSelectionTarget
commonParameters() - Method in class jdistlib.inference.SparseSubsetState
commonSquareSums() - Method in class jdistlib.inference.SparseSubsetCheckpoint
commonStandardDeviation(int) - Method in class jdistlib.inference.SparseSubsetSummary
commonSums() - Method in class jdistlib.inference.SparseSubsetCheckpoint
compact() - Method in class jdistlib.math.Polynomial: Compacts the representation of this polynomial.
compare(LooModelComparison.NamedResult...) - Static method in class jdistlib.inference.LooModelComparison
compile(String) - Static method in class jdistlib.inference.lang.ModelScript
compile(String, Path) - Static method in class jdistlib.inference.lang.ModelCompilationCache
compile(String, Map<String, double[]>) - Static method in class jdistlib.inference.lang.ModelScript
compile(String, Map<String, double[]>, ExternalFunctionRegistry) - Static method in class jdistlib.inference.lang.ModelScript: Compiles with Java bindings for forward-declared external functions.
compile(Map<String, double[]>) - Method in interface jdistlib.inference.lang.GeneratedModelFactory
CompiledModelScript - Class in jdistlib.inference.lang: Compiled model plus deterministic or random generated-quantity program.
compileStan(String) - Static method in class jdistlib.inference.lang.ModelScript: Compiles a data-free Stan source program supported by the compatibility core.
compileStan(String, Map<String, double[]>) - Static method in class jdistlib.inference.lang.ModelScript: Compiles ordinary Stan syntax supported by the Java-native compatibility core.
compileStan(String, Map<String, double[]>, ExternalFunctionRegistry) - Static method in class jdistlib.inference.lang.ModelScript: Compiles Stan-compatible source with Java external-function bindings.
COMPLETE - Enum constant in enum class jdistlib.inference.WarmupSchedule.Phase
completedIterations() - Method in class jdistlib.inference.ChainCheckpoint
completedIterations() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
completedTransitions() - Method in class jdistlib.inference.SparseSubsetCheckpoint
Complex - Class in jdistlib.math: Immutable double-precision complex value used by Java integrations.
Complex(double, double) - Constructor for class jdistlib.math.Complex
components() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition
components() - Method in class jdistlib.accelerator.SingularValueDecomposition
ComponentWiseMetropolis - Class in jdistlib.inference: Gaussian Metropolis sweeps with independently adapted coordinate scales.
ComponentWiseMetropolis() - Constructor for class jdistlib.inference.ComponentWiseMetropolis
compoundSum(GenericDistribution, GenericDistribution, int, int, long) - Static method in class jdistlib.finance.DistributionAggregation
compute(PointwiseLogLikelihoodDraws) - Static method in class jdistlib.inference.PsisLoo
compute(PointwiseLogLikelihoodDraws) - Static method in class jdistlib.inference.Waic
compute(PointwiseLogLikelihoodDraws, PsisLoo.ExactLooFallback) - Static method in class jdistlib.inference.PsisLoo
Compute - Enum Class in jdistlib.accelerator: Selects automatic, CPU, or required accelerator execution.
ComputeApi - Enum Class in jdistlib.accelerator: Concrete compute API or native library family.
ComputeBackedLogDensity - Interface in jdistlib.inference: A differentiable target whose numerical evaluation is bound to a compute backend.
computeBackend() - Method in class jdistlib.inference.AcceleratedLogisticRegression
computeBackend() - Method in interface jdistlib.inference.ComputeBackedLogDensity
computeBackend() - Method in class jdistlib.inference.InferenceCliOptions
computeBackend() - Method in class jdistlib.inference.RunManifest
computeBackend() - Method in class jdistlib.inference.SamplingOptions: Compute policy for accelerator-aware numerical targets and operations.
computeBackend(Compute) - Method in class jdistlib.inference.SamplingOptions.Builder: Selects automatic, CPU, or a required accelerator backend.
ComputeBackend - Interface in jdistlib.accelerator: Optional backend for vector, dense-linear-algebra, and batched likelihood work.
ComputeBackends - Class in jdistlib.accelerator: Discovers optional accelerator providers without making them core dependencies.
ComputeCapabilities - Class in jdistlib.accelerator: Immutable compute-device capabilities relevant to statistical kernels.
ComputeCapabilities(String, String, boolean, boolean, long) - Constructor for class jdistlib.accelerator.ComputeCapabilities
ComputeCapabilities(String, String, boolean, boolean, long, boolean, boolean, boolean) - Constructor for class jdistlib.accelerator.ComputeCapabilities
ComputeCapabilities(String, String, boolean, boolean, long, boolean, boolean, boolean, boolean, boolean, boolean) - Constructor for class jdistlib.accelerator.ComputeCapabilities
ComputeCapabilities(String, String, boolean, boolean, long, boolean, boolean, boolean, boolean, boolean, boolean, boolean, boolean) - Constructor for class jdistlib.accelerator.ComputeCapabilities
computeDevice() - Method in class jdistlib.inference.RunManifest
ComputeDeviceInfo - Class in jdistlib.accelerator: Immutable backend, runtime, driver, and device provenance.
ComputeDeviceInfo(String, String, ComputeApi, String, String, String, String, String, String, long) - Constructor for class jdistlib.accelerator.ComputeDeviceInfo
ComputeNuts - Enum Class in jdistlib.inference: Controls whether NUTS target evaluation may or must use an accelerator.
computePolicy() - Method in class jdistlib.inference.RunManifest
ComputeSelection - Class in jdistlib.accelerator: Selected compute backend, device provenance, and ownership for one workflow.
conditionalCoefficientMean(int) - Method in class jdistlib.inference.SparseSubsetSummary
conditionalCoefficientStandardDeviation(int) - Method in class jdistlib.inference.SparseSubsetSummary
ConditionalDistribution - Class in jdistlib.finance: Exact scalar law conditional on lower < X <= upper.
ConditionalDistribution(GenericDistribution, double, double) - Constructor for class jdistlib.finance.ConditionalDistribution
conditionalFirstGivenSecond(double, double) - Method in class jdistlib.PairCopula: Returns P[U1 <= first | U2 = second].
conditionalSecondGivenFirst(double, double) - Method in class jdistlib.PairCopula: Returns P[U2 <= second | U1 = first].
configureAdaptiveRejectionSampling(UnivariateFunction, int, int, double...) - Method in class jdistlib.NumericalContinuousDistribution: Configures adaptive rejection under a caller-certified log-concavity promise.
configureRejectionSampling(RejectionEnvelope, int) - Method in class jdistlib.NumericalContinuousDistribution: Configures rejection-envelope sampling for subsequent NumericalContinuousDistribution.random() calls.
configureUniformRejectionSampling(double, int) - Method in class jdistlib.NumericalContinuousDistribution: Configures a uniform rejection envelope over this finite support.
conjugate() - Method in class jdistlib.math.Complex
constant(double) - Static method in class jdistlib.DiscreteTailBounds: Uses a fixed finite upper bound, which must include the first term.
constant(double) - Method in class jdistlib.inference.autodiff.ReverseTape
constant(double, double[], double[], double, double, double) - Static method in class jdistlib.math.approx.ApproximationFunction: Constant approximation
CONSTANT - Enum constant in enum class jdistlib.math.approx.ApproximationType
Constants - Class in jdistlib.math: Class defining constants.
Constants() - Constructor for class jdistlib.math.Constants
constrain(double[]) - Method in class jdistlib.inference.BayesianModel
constrain(double[], int, double[], int) - Method in interface jdistlib.inference.ParameterConstraint: Constrains a slice and returns its log absolute Jacobian determinant.
constrained() - Method in class jdistlib.inference.DivergenceLocation
constrainedDimension() - Method in class jdistlib.inference.ModelState
constrainedDimension() - Method in interface jdistlib.inference.ParameterConstraint
constrainedDimension() - Method in class jdistlib.inference.ParameterSpec
constrainedOffset() - Method in class jdistlib.inference.ParameterSpec
constrainedOffset(String) - Method in class jdistlib.inference.ModelState
constrainedSamples(BayesianModel) - Method in class jdistlib.inference.ChainResult
constraint() - Method in class jdistlib.inference.ParameterSpec
constraintCount() - Method in interface jdistlib.inference.solver.HolonomicDaeSystem: Number of independent position constraints.
constraints(double, double[], double[], double[], double[]) - Method in interface jdistlib.inference.solver.HolonomicDaeSystem: Writes g(time, position) = 0 into residual.
Constraints - Class in jdistlib.inference: Standard parameter constraints and their Jacobian-aware transforms.
constructionPolicy(ConstructionPolicy) - Method in class jdistlib.FunctionAnalysisOptions.Builder
constructionPolicy(ConstructionPolicy) - Method in class jdistlib.NumericalContinuousDistribution.Builder
ConstructionPolicy - Enum Class in jdistlib: Determines which advisory findings prevent analyzed construction.
contains(double) - Method in class jdistlib.finance.TransformDomain
contains(double) - Method in class jdistlib.inference.CoordinateSupport
contains(double) - Method in class jdistlib.NumericalSupport.Interval
contains(double[]) - Method in class jdistlib.inference.MixedStateSpace
contains(String) - Method in class jdistlib.inference.ModelData
containsContinuous(double) - Method in class jdistlib.NumericalSupport
continuous(GenericDistribution) - Static method in class jdistlib.CopulaMarginal: Declares an atom-free marginal.
CONTINUOUS - Enum constant in enum class jdistlib.CopulaMarginal.Kind
ContinuousBlockMetropolisKernel - Class in jdistlib.inference: Gaussian random-walk update of a continuous block conditional on all other coordinates.
ContinuousBlockMetropolisKernel(int[], double) - Constructor for class jdistlib.inference.ContinuousBlockMetropolisKernel
ContinuousBlockMetropolisKernel(int[], double[]) - Constructor for class jdistlib.inference.ContinuousBlockMetropolisKernel
continuousCoordinates() - Method in class jdistlib.inference.MixedStateSpace
converged() - Method in class jdistlib.inference.OptimizationResult
converged() - Method in class jdistlib.inference.PredictiveStacking.Result
CONVERGED - Enum constant in enum class jdistlib.finance.ImpliedVolatilityResult.Status
convolution(GenericDistribution, GenericDistribution, int, long) - Static method in class jdistlib.finance.DistributionAggregation
coordinate() - Method in class jdistlib.inference.GeometryAdvice
coordinate() - Method in class jdistlib.inference.PrecisionGoal
CoordinateInsertionTransformation - Class in jdistlib.inference: Unit-Jacobian birth/death mapping that inserts or removes one parameter coordinate.
CoordinateInsertionTransformation(long, long, int) - Constructor for class jdistlib.inference.CoordinateInsertionTransformation
coordinates() - Method in class jdistlib.inference.ColumnarDraws
CoordinateSplitTransformation - Class in jdistlib.inference: Split/merge map x,u to x+u,x-u with forward log-Jacobian log(2).
CoordinateSplitTransformation(long, long, int) - Constructor for class jdistlib.inference.CoordinateSplitTransformation
CoordinateSupport - Class in jdistlib.inference: Typed support for one coordinate in a mixed continuous/discrete state.
CoordinateSupport.Kind - Enum Class in jdistlib.inference
Copula - Interface in jdistlib: A copula on the unit hypercube.
CopulaDiagnostics - Class in jdistlib: Immutable classification of a proposed copula evaluation point.
CopulaDiagnostics.Classification - Enum Class in jdistlib: Location of the point relative to the unit hypercube.
CopulaDistribution - Class in jdistlib: Joint distribution composed from a copula and continuous univariate marginals.
CopulaDistribution(Copula, GenericDistribution...) - Constructor for class jdistlib.CopulaDistribution
CopulaFamily - Enum Class in jdistlib: Built-in families supported by dependence fitting and selection.
CopulaFitOptions - Class in jdistlib: Controls rank-based initialization and optional likelihood refinement.
CopulaFitOptions() - Constructor for class jdistlib.CopulaFitOptions
CopulaFitOptions.Method - Enum Class in jdistlib
CopulaFitResult - Class in jdistlib: Result of fitting one copula family to pseudo-observations.
CopulaFitResult.Status - Enum Class in jdistlib
CopulaFitter - Class in jdistlib: Rank transformation and dependence fitting for the built-in copula families.
CopulaLikelihoodDiagnostics - Class in jdistlib: Row-level log-density and unit-cube boundary diagnostics for a copula model.
CopulaLikelihoodDiagnostics.Status - Enum Class in jdistlib
CopulaLogLikelihoodResult - Class in jdistlib: Auditable likelihood aggregation for continuous, discrete, or mixed data.
CopulaLogLikelihoodResult.Status - Enum Class in jdistlib
CopulaMarginal - Class in jdistlib: A scalar marginal together with its continuity/atom contract.
CopulaMarginal.Kind - Enum Class in jdistlib: Measure used by a joint likelihood contribution.
CopulaMeasureOptions - Class in jdistlib: Numerical controls for mixed continuous/discrete copula likelihoods.
CopulaMeasureOptions() - Constructor for class jdistlib.CopulaMeasureOptions
CopulaMeasureResult - Class in jdistlib: Joint density, mass, or mixed-measure likelihood contribution.
CopulaMeasureResult.Status - Enum Class in jdistlib
CopulaSelectionCriterion - Enum Class in jdistlib: Information criterion used by automatic copula-family selection.
CopulaSelectionResult - Class in jdistlib: Ranked family fits and the selected successful candidate.
CopulaSelector - Class in jdistlib: Fits candidate families and ranks them by AIC or BIC.
CopulaTailAnalysis - Class in jdistlib.finance: Tail dependence, finite-level concentration, and bivariate stress regions.
COPY - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
copyBackward(double[], int, double[], int, int) - Static method in class jdistlib.generic.GenericDistribution: Whether an in-place, right-shifted operation must run from right to left.
correlationFromKendallsTau(double[][]) - Static method in class jdistlib.GaussianCopula: Converts a Kendall tau matrix to its elliptical correlation matrix.
correlationMatrix(int) - Static method in class jdistlib.inference.Constraints: Stan-compatible correlation-matrix (LKJ/CPC) transform, stored row-major.
cos() - Method in class jdistlib.math.Complex
cos(int) - Method in class jdistlib.inference.autodiff.ReverseTape
cosh() - Method in class jdistlib.math.Complex
COSINE - Enum constant in enum class jdistlib.math.density.Kernel
cosInversion(TransformDistribution, double, double, int, int) - Static method in class jdistlib.finance.DistributionAggregation: Fourier-cosine density discretization on a caller-declared finite interval.
cospi(double) - Static method in class jdistlib.math.MathFunctions
count(int, int) - Method in class jdistlib.SignRank
count(int, int, int) - Method in class jdistlib.Wilcoxon
countNearBoundary(double) - Method in class jdistlib.CopulaLikelihoodDiagnostics
countRejected(double[], double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Returns the number of hypotheses rejected at the requested level.
countRejected(double[], double, MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Returns the rejection count for a declared total family size.
countRejectedLog(double[], double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Returns the rejection count for natural-log p-values.
countRejectedLog(double[], double, MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Returns the log-p rejection count for a declared total family size.
covarianceCount() - Method in class jdistlib.inference.SamplerCheckpoint
covarianceMatrix(int) - Static method in class jdistlib.inference.Constraints: Stan-compatible covariance-matrix transform, stored row-major.
covarianceMean() - Method in class jdistlib.inference.SamplerCheckpoint
covarianceProducts() - Method in class jdistlib.inference.SamplerCheckpoint
CPU - Enum constant in enum class jdistlib.accelerator.Compute: Always use the deterministic CPU reference implementation.
CpuComputeBackend - Class in jdistlib.accelerator: Deterministic CPU reference implementation for every accelerated primitive.
CpuComputeBackend() - Constructor for class jdistlib.accelerator.CpuComputeBackend
CQUAD - Enum constant in enum class jdistlib.math.IntegrationOptions.Method: Doubly-adaptive Clenshaw-Curtis quadrature on finite intervals.
cramer_von_mises_statistic(double[], GenericDistribution) - Static method in class jdistlib.disttest.DistributionTest: One-sample Cramer-von Mises statistic against a fully specified continuous reference distribution.
cramer_von_mises_test(double[], double[]) - Static method in class jdistlib.disttest.DistributionTest: Two-sample Cramer-von Mises test using a deterministic permutation p-value.
cramer_von_mises_test(double[], double[], int, RandomEngine) - Static method in class jdistlib.disttest.DistributionTest: Two-sample Cramer-von Mises test with caller-controlled permutations.
cramer_von_mises_test(double[], GenericDistribution) - Static method in class jdistlib.disttest.DistributionTest: One-sample Cramer-von Mises test using a deterministic parametric bootstrap.
cramer_von_mises_test(double[], GenericDistribution, int, RandomEngine) - Static method in class jdistlib.disttest.DistributionTest: One-sample Cramer-von Mises test with caller-controlled bootstrap sampling.
cramer_vonmises_pvalue(double, int) - Static method in class jdistlib.disttest.NormalityTest
cramer_vonmises_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest
cramer_vonmises_statistic(double[], double[]) - Static method in class jdistlib.disttest.DistributionTest: Two-sample Cramer-Von Mises test
create() - Method in interface jdistlib.inference.ReversibleJumpSamplerFactory
create(double[]) - Method in interface jdistlib.inference.AdaptiveRejectionGibbsKernel.ConditionalFactory
create(Compute, double[][], double[], double) - Static method in class jdistlib.inference.AcceleratedLogisticRegression: Selects a backend directly for vectorized or regular many-chain workflows.
create(Sampler, String, SamplingOptions, long, long, long) - Static method in class jdistlib.inference.RunManifest
create(Sampler, LogDensity, String, SamplingOptions, long, long, long) - Static method in class jdistlib.inference.RunManifest: Creates a manifest that records the target's concrete compute backend when available.
create_instance_from_mu(double, double) - Static method in class jdistlib.NegBinomial
create_random_state() - Static method in class jdistlib.Binomial
create_random_state() - Static method in class jdistlib.HyperGeometric
create_random_state() - Static method in class jdistlib.Poisson
create_random_state(Binomial.BinomialKind) - Static method in class jdistlib.Binomial
criterion() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
criterion(AdaptiveStaticHmcOptions.Criterion) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
CSR_ANALYZE - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_GEMM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_MM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_MV - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_POTRF - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_REFACTOR - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_SOLVE - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CSR_TRSV - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
CsrMatrix - Class in jdistlib.matrix: Immutable one-based compressed-row sparse matrix compatible with Stan CSR arrays.
CsrMatrix(int, int, double[], int[], int[]) - Constructor for class jdistlib.matrix.CsrMatrix
CUDA - Enum constant in enum class jdistlib.accelerator.Compute: Require the optional CUDA provider.
CUDA - Enum constant in enum class jdistlib.accelerator.ComputeApi
cumsum(double[]) - Static method in class jdistlib.math.VectorMath
cumsum(int[]) - Static method in class jdistlib.math.VectorMath
cumulant(GenericDistribution, int) - Static method in class jdistlib.finance.DistributionTransforms: Numerical cumulant obtained by centered finite differences of log M(t).
cumulative(double) - Method in class jdistlib.generic.GenericDistribution: Assume lower tail and non-log
cumulative(double) - Method in class jdistlib.NumericalCdfTable
cumulative(double[]) - Method in class jdistlib.BB1Copula
cumulative(double[]) - Method in class jdistlib.ClaytonCopula
cumulative(double[]) - Method in interface jdistlib.Copula: Copula distribution function at u.
cumulative(double[]) - Method in class jdistlib.CopulaDistribution: Joint lower-orthant CDF.
cumulative(double[]) - Method in class jdistlib.CVineCopula
cumulative(double[]) - Method in class jdistlib.DVineCopula
cumulative(double[]) - Method in class jdistlib.FrankCopula
cumulative(double[]) - Method in class jdistlib.GaussianCopula
cumulative(double[]) - Method in class jdistlib.generic.GenericDistribution: Assume lower tail and non-log
cumulative(double[]) - Method in class jdistlib.GumbelCopula
cumulative(double[]) - Method in class jdistlib.IndependenceCopula
cumulative(double[]) - Method in class jdistlib.JoeCopula
cumulative(double[]) - Method in class jdistlib.MixedCopulaDistribution
cumulative(double[]) - Method in class jdistlib.RotatedCopula
cumulative(double[]) - Method in class jdistlib.StudentTCopula
cumulative(double[], boolean, boolean) - Method in class jdistlib.generic.GenericDistribution
cumulative(double[], double[]) - Static method in class jdistlib.Dirichlet
cumulative(double[], double[], double[][]) - Static method in class jdistlib.MultivariateCauchy
cumulative(double[], double[], double[][]) - Static method in class jdistlib.MultivariateLaplace
cumulative(double[], double[], double[][]) - Static method in class jdistlib.MultivariateLogNormal
cumulative(double[], double[], double[][]) - Static method in class jdistlib.MultivariateNormal
cumulative(double[], double[], double[][], double) - Static method in class jdistlib.MultivariatePowerExponential
cumulative(double[], double[], double[][], double) - Static method in class jdistlib.MultivariateStudentT
cumulative(double[], double[], double[][], double, MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariatePowerExponential: Computes P(X[i] <= upper[i], all i).
cumulative(double[], double[], double[][], double, MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateStudentT: Computes P[X[i] <= upper[i] for every i].
cumulative(double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateCauchy
cumulative(double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateLaplace: Computes P(X[i] <= upper[i], all i).
cumulative(double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateLogNormal
cumulative(double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateNormal: Computes P[X[i] <= upper[i] for every i].
cumulative(double[], double[], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.Dirichlet: Computes P(X[i] <= upper[i], all i) on the simplex.
cumulative(double, boolean, boolean) - Method in class jdistlib.Ansari
cumulative(double, boolean, boolean) - Method in class jdistlib.Arcsine
cumulative(double, boolean, boolean) - Method in class jdistlib.AsymmetricLaplace
cumulative(double, boolean, boolean) - Method in class jdistlib.Beta
cumulative(double, boolean, boolean) - Method in class jdistlib.BetaBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.BetaNegativeBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.BetaPrime
cumulative(double, boolean, boolean) - Method in class jdistlib.Binomial
cumulative(double, boolean, boolean) - Method in class jdistlib.BirnbaumSaunders
cumulative(double, boolean, boolean) - Method in class jdistlib.Categorical
cumulative(double, boolean, boolean) - Method in class jdistlib.Cauchy
cumulative(double, boolean, boolean) - Method in class jdistlib.CensoredDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.Chi
cumulative(double, boolean, boolean) - Method in class jdistlib.ChiSquare
cumulative(double, boolean, boolean) - Method in class jdistlib.DiscreteLaplace
cumulative(double, boolean, boolean) - Method in class jdistlib.DiscreteWeibull
cumulative(double, boolean, boolean) - Method in class jdistlib.Empirical
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.Extreme
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.Fretchet
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.GeneralizedPareto
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.GEV
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.Gumbel
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.Order
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.Rayleigh
cumulative(double, boolean, boolean) - Method in class jdistlib.evd.ReverseWeibull
cumulative(double, boolean, boolean) - Method in class jdistlib.Exponential
cumulative(double, boolean, boolean) - Method in class jdistlib.ExponentiallyModifiedGaussian
cumulative(double, boolean, boolean) - Method in class jdistlib.F
cumulative(double, boolean, boolean) - Method in class jdistlib.FellerPareto
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.ConditionalDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.DelaporteDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.EmpiricalDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.FiniteGridDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.OptionImpliedDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.OrderStatisticDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.PolyaAeppliDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.StableDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.CgmyDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.LevyIncrementDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.MeixnerDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.NormalTemperedStableDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.finance.VarianceGammaDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.FoldedNormal
cumulative(double, boolean, boolean) - Method in class jdistlib.Gamma
cumulative(double, boolean, boolean) - Method in class jdistlib.GeneralizedBetaSecondKind
cumulative(double, boolean, boolean) - Method in class jdistlib.GeneralizedF
cumulative(double, boolean, boolean) - Method in class jdistlib.GeneralizedGamma
cumulative(double, boolean, boolean) - Method in class jdistlib.generic.GenericDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.Geometric
cumulative(double, boolean, boolean) - Method in class jdistlib.Gompertz
cumulative(double, boolean, boolean) - Method in class jdistlib.HalfCauchy
cumulative(double, boolean, boolean) - Method in class jdistlib.HalfNormal
cumulative(double, boolean, boolean) - Method in class jdistlib.HalfT
cumulative(double, boolean, boolean) - Method in class jdistlib.Huber
cumulative(double, boolean, boolean) - Method in class jdistlib.HurdleNegativeBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.HurdlePoisson
cumulative(double, boolean, boolean) - Method in class jdistlib.HyperGeometric
cumulative(double, boolean, boolean) - Method in class jdistlib.InvGamma
cumulative(double, boolean, boolean) - Method in class jdistlib.InvNormal
cumulative(double, boolean, boolean) - Method in class jdistlib.Kendall
cumulative(double, boolean, boolean) - Method in class jdistlib.Kumaraswamy
cumulative(double, boolean, boolean) - Method in class jdistlib.Laplace
cumulative(double, boolean, boolean) - Method in class jdistlib.Levy
cumulative(double, boolean, boolean) - Method in class jdistlib.Lindley
cumulative(double, boolean, boolean) - Method in class jdistlib.Logarithmic
cumulative(double, boolean, boolean) - Method in class jdistlib.Logistic
cumulative(double, boolean, boolean) - Method in class jdistlib.LogitNormal
cumulative(double, boolean, boolean) - Method in class jdistlib.LogLogistic
cumulative(double, boolean, boolean) - Method in class jdistlib.LogNormal
cumulative(double, boolean, boolean) - Method in class jdistlib.Makeham
cumulative(double, boolean, boolean) - Method in class jdistlib.Maxwell
cumulative(double, boolean, boolean) - Method in class jdistlib.MaxwellBoltzmann
cumulative(double, boolean, boolean) - Method in class jdistlib.MixtureDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.MonotoneTransformDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.Nakagami
cumulative(double, boolean, boolean) - Method in class jdistlib.NegativeHypergeometric
cumulative(double, boolean, boolean) - Method in class jdistlib.NegBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.NonCentralBeta
cumulative(double, boolean, boolean) - Method in class jdistlib.NonCentralChiSquare
cumulative(double, boolean, boolean) - Method in class jdistlib.NonCentralF
cumulative(double, boolean, boolean) - Method in class jdistlib.NonCentralT
cumulative(double, boolean, boolean) - Method in class jdistlib.Normal
cumulative(double, boolean, boolean) - Method in class jdistlib.NumericalContinuousDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.NumericalDiscreteDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.NumericalPiecewiseDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.PhaseType
cumulative(double, boolean, boolean) - Method in class jdistlib.Poisson
cumulative(double, boolean, boolean) - Method in class jdistlib.PoissonBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.PoissonInverseGaussian
cumulative(double, boolean, boolean) - Method in class jdistlib.PositiveNormal
cumulative(double, boolean, boolean) - Method in class jdistlib.Rice
cumulative(double, boolean, boolean) - Method in class jdistlib.SignRank
cumulative(double, boolean, boolean) - Method in class jdistlib.SinhArcsinh
cumulative(double, boolean, boolean) - Method in class jdistlib.Skellam
cumulative(double, boolean, boolean) - Method in class jdistlib.SkewedT
cumulative(double, boolean, boolean) - Method in class jdistlib.Slash
cumulative(double, boolean, boolean) - Method in class jdistlib.Spearman
cumulative(double, boolean, boolean) - Method in class jdistlib.T
cumulative(double, boolean, boolean) - Method in class jdistlib.Triangular
cumulative(double, boolean, boolean) - Method in class jdistlib.TruncatedContinuousDistribution
cumulative(double, boolean, boolean) - Method in class jdistlib.Tukey
cumulative(double, boolean, boolean) - Method in class jdistlib.TukeyLambda
cumulative(double, boolean, boolean) - Method in class jdistlib.Tweedie
cumulative(double, boolean, boolean) - Method in class jdistlib.Uniform
cumulative(double, boolean, boolean) - Method in class jdistlib.Weibull
cumulative(double, boolean, boolean) - Method in class jdistlib.Wilcoxon
cumulative(double, boolean, boolean) - Method in class jdistlib.ZeroInflatedNegativeBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.ZeroInflatedPoisson
cumulative(double, boolean, boolean) - Method in class jdistlib.ZeroTruncatedNegativeBinomial
cumulative(double, boolean, boolean) - Method in class jdistlib.ZeroTruncatedPoisson
cumulative(double, boolean, boolean) - Method in class jdistlib.Zipf
cumulative(double, double[], boolean, boolean) - Static method in class jdistlib.PoissonBinomial
cumulative(double, double[], double[][], boolean, boolean) - Static method in class jdistlib.PhaseType
cumulative(double, double[], double[], boolean, boolean) - Static method in class jdistlib.Categorical
cumulative(double, double, boolean) - Static method in class jdistlib.evd.Rayleigh
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Chi
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.ChiSquare
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Exponential
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Geometric
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.HalfCauchy
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.HalfNormal
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Lindley
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Logarithmic
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Maxwell
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.MaxwellBoltzmann
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.Poisson
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.T
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.TukeyLambda
cumulative(double, double, boolean, boolean) - Static method in class jdistlib.ZeroTruncatedPoisson
cumulative(double, double, double) - Static method in class jdistlib.Levy
cumulative(double, double, double) - Static method in class jdistlib.Normal
cumulative(double, double, double, boolean) - Static method in class jdistlib.evd.Gumbel
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Arcsine
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Beta
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.BetaPrime
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Binomial
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Cauchy
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.DiscreteLaplace
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.DiscreteWeibull
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.F
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Gamma
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Gompertz
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.HalfT
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.HurdlePoisson
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.InvGamma
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.InvNormal
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Kumaraswamy
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Laplace
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Levy
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Logistic
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.LogitNormal
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.LogLogistic
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.LogNormal
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Nakagami
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.NegBinomial
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralChiSquare
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralT
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Normal
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.PoissonInverseGaussian
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.PositiveNormal
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Rice
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Skellam
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.SkewedT
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Slash
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Uniform
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.Weibull
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.ZeroInflatedPoisson
cumulative(double, double, double, boolean, boolean) - Static method in class jdistlib.ZeroTruncatedNegativeBinomial
cumulative(double, double, double, double, boolean) - Static method in class jdistlib.evd.Fretchet
cumulative(double, double, double, double, boolean) - Static method in class jdistlib.evd.GeneralizedPareto
cumulative(double, double, double, double, boolean) - Static method in class jdistlib.evd.GEV
cumulative(double, double, double, double, boolean) - Static method in class jdistlib.evd.ReverseWeibull
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.AsymmetricLaplace
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.BetaBinomial: Cumulative.
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.BetaNegativeBinomial
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.BirnbaumSaunders
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.ExponentiallyModifiedGaussian
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.GeneralizedGamma
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Huber
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.HurdleNegativeBinomial
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.HyperGeometric
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Makeham
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.NegativeHypergeometric
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralBeta
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralF
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Triangular
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Tukey: function ptukey() [was qprob() ]:
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Tweedie: Returns the Tweedie distribution function.
cumulative(double, double, double, double, boolean, boolean) - Static method in class jdistlib.ZeroInflatedNegativeBinomial
cumulative(double, double, double, double, double) - Static method in class jdistlib.Wiener: Defective CDF matching the upper-boundary density component.
cumulative(double, double, double, double, double, boolean) - Static method in class jdistlib.BivariatePoisson: Returns P[X <= x, Y <= y].
cumulative(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.FoldedNormal
cumulative(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.GeneralizedBetaSecondKind
cumulative(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.GeneralizedF
cumulative(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.SinhArcsinh
cumulative(double, double, double, double, double, double, boolean) - Static method in class jdistlib.BivariateLogistic: Returns P[X1 <= q1, X2 <= q2].
cumulative(double, double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.FellerPareto
cumulative(double, int) - Static method in class jdistlib.Kendall: Cumulative density function of Kendall distribution.
cumulative(double, int, boolean) - Static method in class jdistlib.Spearman: Spearman exact cumulative distribution function for n <= 22.
cumulative(double, GenericDistribution, int, boolean, boolean) - Static method in class jdistlib.evd.Extreme
cumulative(double, GenericDistribution, int, int, boolean, boolean) - Static method in class jdistlib.evd.Order
cumulative(double, GenericDistribution, int, int, boolean, boolean, boolean) - Static method in class jdistlib.evd.Order
cumulative(int[], int[], int) - Static method in class jdistlib.MultivariateHypergeometric: Exact lower-orthant probability P(X[i] <= upper[i], all i).
cumulative(int[], int, double[]) - Static method in class jdistlib.DirichletMultinomial: Exact lower-orthant probability P(X[i] <= upper[i], all i).
cumulative(int[], int, double[]) - Static method in class jdistlib.Multinomial: Exact lower-orthant probability P(X[i] <= upper[i], all i).
cumulative(int[], int, int) - Static method in class jdistlib.Ansari
cumulative(int[], int, int, boolean) - Static method in class jdistlib.Ansari
cumulative(int, boolean, boolean) - Method in class jdistlib.SignRank
cumulative(int, boolean, boolean) - Method in class jdistlib.Wilcoxon
cumulative(int, int, double, boolean, boolean) - Static method in class jdistlib.Zipf
cumulative(int, int, int) - Static method in class jdistlib.Ansari
cumulative(int, int, int, boolean) - Static method in class jdistlib.Ansari
cumulative(int, int, int, double[][][]) - Static method in class jdistlib.Ansari
cumulative(int, int, int, double[][][], boolean) - Static method in class jdistlib.Ansari
cumulative(TransformDistribution, double) - Static method in class jdistlib.finance.DistributionTransforms: Gil-Pelaez inversion of a characteristic function.
cumulative_as89(double, int, boolean) - Static method in class jdistlib.Spearman: Spearman cumulative distribution.
cumulative_hazard(double) - Method in class jdistlib.generic.GenericDistribution: Cumulative hazard function, which is basically -ln(1-CDF).
cumulative_hazard(double[]) - Method in class jdistlib.generic.GenericDistribution
cumulative_mu(double, double, double, boolean, boolean) - Static method in class jdistlib.NegBinomial
cumulative_raw(double, double, double, boolean, boolean) - Static method in class jdistlib.Beta
cumulative_raw(double, double, double, double, double) - Static method in class jdistlib.NonCentralBeta
cumulative_raw(double, double, double, double, double, int, boolean, boolean) - Static method in class jdistlib.NonCentralChiSquare
cumulative_standard(double) - Static method in class jdistlib.Levy
cumulative_standard(double) - Static method in class jdistlib.Normal
cumulative_t(double, int, boolean) - Static method in class jdistlib.Spearman: Spearman cumulative distribution function, approximation using T (df=n-2)
cumulative_tau(double, int) - Static method in class jdistlib.Kendall: Cumulative distribution of Kendall distribution
cumulativeAdaptive(TransformDistribution, double, FourierInversionOptions) - Static method in class jdistlib.finance.DistributionTransforms: Adaptive Gil-Pelaez inversion with explicit truncation/work controls.
cumulativeCached(double, boolean, boolean) - Method in class jdistlib.NumericalContinuousDistribution: Evaluates through the reusable CDF table.
cumulativeHazard(double, double, double, boolean) - Static method in class jdistlib.Gompertz: Returns the cumulative hazard.
cumulativeInto(double[], int, double[], int, int, boolean, boolean) - Method in class jdistlib.generic.GenericDistribution: Evaluates CDF values into caller-owned storage.
cumulativeInto(double[], int, double[], int, int, boolean, boolean) - Method in class jdistlib.NumericalContinuousDistribution: Batch CDF evaluation reuses the monotone table for ordinary probabilities.
cumulativeResult(double) - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution: CDF plus a deterministic quadrature-difference error estimate.
cumulativeResult(double) - Method in class jdistlib.finance.CgmyDistribution
cumulativeResult(double) - Method in class jdistlib.finance.LevyIncrementDistribution
cumulativeResult(double) - Method in class jdistlib.finance.MeixnerDistribution
cumulativeResult(double) - Method in class jdistlib.finance.NormalTemperedStableDistribution
cumulativeResult(double) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
cumulativeResult(double[], int, RandomEngine) - Method in class jdistlib.CVineCopula: Estimates the lower-orthant CDF with caller-owned randomization.
cumulativeResult(double[], int, RandomEngine) - Method in class jdistlib.DVineCopula
cumulativeResult(double[], int, RandomEngine) - Method in interface jdistlib.VineCopula: Estimates the lower-orthant CDF and reports Monte Carlo uncertainty.
customBinary(int, int, double, double, double) - Method in class jdistlib.inference.autodiff.ReverseTape: Creates a binary node from a caller-supplied value and exact local derivatives.
customUnary(int, double, double) - Method in class jdistlib.inference.autodiff.ReverseTape: Creates a unary node from a caller-supplied value and exact local derivative.
CV - Enum constant in enum class jdistlib.math.spline.SmoothSplineCriterion
CV(double[], int, double, double, double, boolean) - Static method in class jdistlib.math.density.Bandwidth
CVineCopula - Class in jdistlib: Simplified C-vine copula assembled from bivariate conditional copulas.
CVineCopula(PairCopula[]...) - Constructor for class jdistlib.CVineCopula: Creates a C-vine.

D

d - Variable in class jdistlib.HyperGeometric.RandomState
D_VINE - Enum constant in enum class jdistlib.VineStructure
d1mach3 - Static variable in class jdistlib.math.Constants
d1mach4 - Static variable in class jdistlib.math.Constants
DaeSolver - Class in jdistlib.inference.solver: Implicit-Euler solver for index-1 differential-algebraic systems.
DaeSystem - Interface in jdistlib.inference.solver: Differential-algebraic residual F(t, y, y') = 0.
dagostino_pearson_pvalue(double) - Static method in class jdistlib.disttest.NormalityTest
dagostino_pearson_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest: Calculate D'Agostino-Pearson test for normality.
dasum(int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
data() - Method in class jdistlib.inference.BayesianModel
data() - Method in class jdistlib.inference.ModelState
data(String, double...) - Method in class jdistlib.inference.ModelBuilder
DATA - Enum constant in enum class jdistlib.inference.ModelGraph.NodeKind
daxpy(int, double, double[], int, int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dbhStepDown(double[], DiscretePValueDistribution[], double) - Static method in class jdistlib.disttest.DiscreteFdr: Runs the DBH step-down procedure of Döhler, Durand, and Roquain.
dbhStepUp(double[], DiscretePValueDistribution[], double) - Static method in class jdistlib.disttest.DiscreteFdr: Runs the DBH step-up procedure of Döhler, Durand, and Roquain.
DBL_DIG - Static variable in class jdistlib.math.Constants
DBL_EPSILON - Static variable in class jdistlib.math.Constants
DBL_MANT_DIG - Static variable in class jdistlib.math.Constants
DBL_MAX - Static variable in class jdistlib.math.Constants
DBL_MAX_EXP - Static variable in class jdistlib.math.Constants
DBL_MIN - Static variable in class jdistlib.math.Constants
DBL_MIN_EXP - Static variable in class jdistlib.math.Constants
dcopy(int, double[], int, int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dcsrgemm(CsrMatrix, CsrMatrix) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dcsrmm(double, CsrMatrix, double[], int, double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dcsrmv(double, CsrMatrix, double[], double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dcsrpotrf(CsrMatrix, MatrixTriangle) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dcsrpotrf(CsrMatrix, MatrixTriangle, SparseOrdering) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dcsrsv(MatrixTriangle, MatrixTranspose, MatrixDiagonal, CsrMatrix, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
ddot(int, double[], int, int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
Debug - Class in jdistlib.util
Debug() - Constructor for class jdistlib.util.Debug
defaultInitialTrustRegionRadius - Static variable in class jdistlib.math.opt.BobyqaConfig
defaultLambdas() - Static method in class jdistlib.disttest.MultipleTesting: Returns a defensive copy of the default q-value lambda grid.
defaultMaxNumFunctionCall - Static variable in class jdistlib.math.opt.OptimizationConfig
defaults() - Static method in class jdistlib.CdfTableOptions
defaults() - Static method in class jdistlib.CertifiedDiscreteOptions
defaults() - Static method in class jdistlib.finance.FourierInversionOptions
defaults() - Static method in class jdistlib.FunctionAnalysisOptions
defaults() - Static method in class jdistlib.inference.solver.AlgebraicSolver.Options
defaults() - Static method in class jdistlib.inference.solver.OdeSolver.Options
defaults() - Static method in class jdistlib.inference.solver.StiffOdeSolver.Options
defaults() - Static method in class jdistlib.math.IntegrationOptions: Returns R-compatible QUADPACK defaults.
defaults() - Static method in class jdistlib.MomentAnalysisOptions
defaultStoppingTrustRegionRadius - Static variable in class jdistlib.math.opt.BobyqaConfig
DelaporteDistribution - Class in jdistlib.finance: Delaporte count: Poisson(lambda) plus NB(shape, successProbability).
DelaporteDistribution(double, double, double) - Constructor for class jdistlib.finance.DelaporteDistribution
dense() - Static method in class jdistlib.inference.MetricConfiguration
DENSE - Enum constant in enum class jdistlib.inference.MetricConfiguration.Type
denseLinearAlgebra() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether the provider accelerates the public dense BLAS operations.
denseMassMatrix() - Method in class jdistlib.inference.SamplingOptions
denseMassMatrix(boolean) - Method in class jdistlib.inference.SamplingOptions.Builder
density(double[]) - Method in interface jdistlib.Copula: Copula density at an interior point.
density(double[]) - Method in class jdistlib.CopulaDistribution: Joint density.
density(double[]) - Method in class jdistlib.generic.GenericDistribution: Assume non-log
density(double[]) - Static method in class jdistlib.math.density.Density
density(double[][], double, double[][], boolean) - Static method in class jdistlib.Wishart: Density of W_dimension(scale, degreesOfFreedom).
density(double[], boolean) - Method in class jdistlib.generic.GenericDistribution
density(double[], double) - Static method in class jdistlib.math.density.Density
density(double[], double[], boolean) - Static method in class jdistlib.Dirichlet
density(double[], double[], double[][], boolean) - Static method in class jdistlib.MultivariateCauchy
density(double[], double[], double[][], boolean) - Static method in class jdistlib.MultivariateLaplace
density(double[], double[], double[][], boolean) - Static method in class jdistlib.MultivariateLogNormal
density(double[], double[], double[][], boolean) - Static method in class jdistlib.MultivariateNormal
density(double[], double[], double[][], double, boolean) - Static method in class jdistlib.MultivariatePowerExponential
density(double[], double[], double[][], double, boolean) - Static method in class jdistlib.MultivariateStudentT
density(double[], int, double[], boolean) - Static method in class jdistlib.DirichletMultinomial
density(double[], int, double[], boolean) - Static method in class jdistlib.Multinomial
density(double[], Bandwidth, double, Kernel, double[], double, int, double, double, double) - Static method in class jdistlib.math.density.Density
density(double, boolean) - Method in class jdistlib.Ansari
density(double, boolean) - Method in class jdistlib.Arcsine
density(double, boolean) - Method in class jdistlib.AsymmetricLaplace
density(double, boolean) - Method in class jdistlib.Beta
density(double, boolean) - Method in class jdistlib.BetaBinomial
density(double, boolean) - Method in class jdistlib.BetaNegativeBinomial
density(double, boolean) - Method in class jdistlib.BetaPrime
density(double, boolean) - Method in class jdistlib.Binomial
density(double, boolean) - Method in class jdistlib.BirnbaumSaunders
density(double, boolean) - Method in class jdistlib.Categorical
density(double, boolean) - Method in class jdistlib.Cauchy
density(double, boolean) - Method in class jdistlib.CensoredDistribution
density(double, boolean) - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
density(double, boolean) - Method in class jdistlib.Chi
density(double, boolean) - Method in class jdistlib.ChiSquare
density(double, boolean) - Method in class jdistlib.DiscreteLaplace
density(double, boolean) - Method in class jdistlib.DiscreteWeibull
density(double, boolean) - Method in class jdistlib.Empirical
density(double, boolean) - Method in class jdistlib.evd.Extreme
density(double, boolean) - Method in class jdistlib.evd.Fretchet
density(double, boolean) - Method in class jdistlib.evd.GeneralizedPareto
density(double, boolean) - Method in class jdistlib.evd.GEV
density(double, boolean) - Method in class jdistlib.evd.Gumbel
density(double, boolean) - Method in class jdistlib.evd.Order
density(double, boolean) - Method in class jdistlib.evd.Rayleigh
density(double, boolean) - Method in class jdistlib.evd.ReverseWeibull
density(double, boolean) - Method in class jdistlib.Exponential
density(double, boolean) - Method in class jdistlib.ExponentiallyModifiedGaussian
density(double, boolean) - Method in class jdistlib.F
density(double, boolean) - Method in class jdistlib.FellerPareto
density(double, boolean) - Method in class jdistlib.finance.ConditionalDistribution
density(double, boolean) - Method in class jdistlib.finance.DelaporteDistribution
density(double, boolean) - Method in class jdistlib.finance.EmpiricalDistribution
density(double, boolean) - Method in class jdistlib.finance.FiniteGridDistribution
density(double, boolean) - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
density(double, boolean) - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
density(double, boolean) - Method in class jdistlib.finance.OptionImpliedDistribution
density(double, boolean) - Method in class jdistlib.finance.OrderStatisticDistribution
density(double, boolean) - Method in class jdistlib.finance.PolyaAeppliDistribution
density(double, boolean) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
density(double, boolean) - Method in class jdistlib.finance.StableDistribution
density(double, boolean) - Method in class jdistlib.finance.CgmyDistribution
density(double, boolean) - Method in class jdistlib.finance.LevyIncrementDistribution
density(double, boolean) - Method in class jdistlib.finance.MeixnerDistribution
density(double, boolean) - Method in class jdistlib.finance.NormalTemperedStableDistribution
density(double, boolean) - Method in class jdistlib.finance.VarianceGammaDistribution
density(double, boolean) - Method in class jdistlib.FoldedNormal
density(double, boolean) - Method in class jdistlib.Gamma
density(double, boolean) - Method in class jdistlib.GeneralizedBetaSecondKind
density(double, boolean) - Method in class jdistlib.GeneralizedF
density(double, boolean) - Method in class jdistlib.GeneralizedGamma
density(double, boolean) - Method in class jdistlib.generic.GenericDistribution
density(double, boolean) - Method in class jdistlib.Geometric
density(double, boolean) - Method in class jdistlib.Gompertz
density(double, boolean) - Method in class jdistlib.HalfCauchy
density(double, boolean) - Method in class jdistlib.HalfNormal
density(double, boolean) - Method in class jdistlib.HalfT
density(double, boolean) - Method in class jdistlib.Huber
density(double, boolean) - Method in class jdistlib.HurdleNegativeBinomial
density(double, boolean) - Method in class jdistlib.HurdlePoisson
density(double, boolean) - Method in class jdistlib.HyperGeometric
density(double, boolean) - Method in class jdistlib.InvGamma
density(double, boolean) - Method in class jdistlib.InvNormal
density(double, boolean) - Method in class jdistlib.Kendall
density(double, boolean) - Method in class jdistlib.Kumaraswamy
density(double, boolean) - Method in class jdistlib.Laplace
density(double, boolean) - Method in class jdistlib.Levy
density(double, boolean) - Method in class jdistlib.Lindley
density(double, boolean) - Method in class jdistlib.Logarithmic
density(double, boolean) - Method in class jdistlib.Logistic
density(double, boolean) - Method in class jdistlib.LogitNormal
density(double, boolean) - Method in class jdistlib.LogLogistic
density(double, boolean) - Method in class jdistlib.LogNormal
density(double, boolean) - Method in class jdistlib.Makeham
density(double, boolean) - Method in class jdistlib.Maxwell
density(double, boolean) - Method in class jdistlib.MaxwellBoltzmann
density(double, boolean) - Method in class jdistlib.MixtureDistribution
density(double, boolean) - Method in class jdistlib.MonotoneTransformDistribution
density(double, boolean) - Method in class jdistlib.Nakagami
density(double, boolean) - Method in class jdistlib.NegativeHypergeometric
density(double, boolean) - Method in class jdistlib.NegBinomial
density(double, boolean) - Method in class jdistlib.NonCentralBeta
density(double, boolean) - Method in class jdistlib.NonCentralChiSquare
density(double, boolean) - Method in class jdistlib.NonCentralF
density(double, boolean) - Method in class jdistlib.NonCentralT
density(double, boolean) - Method in class jdistlib.Normal
density(double, boolean) - Method in class jdistlib.NumericalContinuousDistribution
density(double, boolean) - Method in class jdistlib.NumericalDiscreteDistribution
density(double, boolean) - Method in class jdistlib.NumericalPiecewiseDistribution
density(double, boolean) - Method in class jdistlib.PhaseType
density(double, boolean) - Method in class jdistlib.Poisson
density(double, boolean) - Method in class jdistlib.PoissonBinomial
density(double, boolean) - Method in class jdistlib.PoissonInverseGaussian
density(double, boolean) - Method in class jdistlib.PositiveNormal
density(double, boolean) - Method in class jdistlib.Rice
density(double, boolean) - Method in class jdistlib.SignRank
density(double, boolean) - Method in class jdistlib.SinhArcsinh
density(double, boolean) - Method in class jdistlib.Skellam
density(double, boolean) - Method in class jdistlib.SkewedT
density(double, boolean) - Method in class jdistlib.Slash
density(double, boolean) - Method in class jdistlib.Spearman: Density.
density(double, boolean) - Method in class jdistlib.T
density(double, boolean) - Method in class jdistlib.Triangular
density(double, boolean) - Method in class jdistlib.TruncatedContinuousDistribution
density(double, boolean) - Method in class jdistlib.Tukey: Density of Tukey HSD distribution using differentials of the cumulative --- WARNING: Untested!
density(double, boolean) - Method in class jdistlib.TukeyLambda
density(double, boolean) - Method in class jdistlib.Tweedie
density(double, boolean) - Method in class jdistlib.Uniform
density(double, boolean) - Method in class jdistlib.Weibull
density(double, boolean) - Method in class jdistlib.Wilcoxon
density(double, boolean) - Method in class jdistlib.ZeroInflatedNegativeBinomial
density(double, boolean) - Method in class jdistlib.ZeroInflatedPoisson
density(double, boolean) - Method in class jdistlib.ZeroTruncatedNegativeBinomial
density(double, boolean) - Method in class jdistlib.ZeroTruncatedPoisson
density(double, boolean) - Method in class jdistlib.Zipf
density(double, double[], boolean) - Static method in class jdistlib.PoissonBinomial
density(double, double[], double[][], boolean) - Static method in class jdistlib.PhaseType
density(double, double[], double[], boolean) - Static method in class jdistlib.Categorical
density(double, double, boolean) - Static method in class jdistlib.Chi
density(double, double, boolean) - Static method in class jdistlib.ChiSquare
density(double, double, boolean) - Static method in class jdistlib.evd.Rayleigh
density(double, double, boolean) - Static method in class jdistlib.Exponential
density(double, double, boolean) - Static method in class jdistlib.Geometric
density(double, double, boolean) - Static method in class jdistlib.HalfCauchy
density(double, double, boolean) - Static method in class jdistlib.HalfNormal
density(double, double, boolean) - Static method in class jdistlib.Lindley
density(double, double, boolean) - Static method in class jdistlib.Logarithmic
density(double, double, boolean) - Static method in class jdistlib.Maxwell
density(double, double, boolean) - Static method in class jdistlib.MaxwellBoltzmann
density(double, double, boolean) - Static method in class jdistlib.Poisson
density(double, double, boolean) - Static method in class jdistlib.T
density(double, double, boolean) - Static method in class jdistlib.TukeyLambda
density(double, double, boolean) - Static method in class jdistlib.ZeroTruncatedPoisson
density(double, double, double, boolean) - Static method in class jdistlib.Arcsine
density(double, double, double, boolean) - Static method in class jdistlib.Beta
density(double, double, double, boolean) - Static method in class jdistlib.BetaPrime
density(double, double, double, boolean) - Static method in class jdistlib.Binomial
density(double, double, double, boolean) - Static method in class jdistlib.Cauchy
density(double, double, double, boolean) - Static method in class jdistlib.DiscreteLaplace
density(double, double, double, boolean) - Static method in class jdistlib.DiscreteWeibull
density(double, double, double, boolean) - Static method in class jdistlib.evd.Gumbel
density(double, double, double, boolean) - Static method in class jdistlib.F
density(double, double, double, boolean) - Static method in class jdistlib.Gamma
density(double, double, double, boolean) - Static method in class jdistlib.Gompertz
density(double, double, double, boolean) - Static method in class jdistlib.HalfT
density(double, double, double, boolean) - Static method in class jdistlib.HurdlePoisson
density(double, double, double, boolean) - Static method in class jdistlib.InvGamma
density(double, double, double, boolean) - Static method in class jdistlib.InvNormal
density(double, double, double, boolean) - Static method in class jdistlib.Kumaraswamy
density(double, double, double, boolean) - Static method in class jdistlib.Laplace
density(double, double, double, boolean) - Static method in class jdistlib.Levy
density(double, double, double, boolean) - Static method in class jdistlib.Logistic
density(double, double, double, boolean) - Static method in class jdistlib.LogitNormal
density(double, double, double, boolean) - Static method in class jdistlib.LogLogistic
density(double, double, double, boolean) - Static method in class jdistlib.LogNormal
density(double, double, double, boolean) - Static method in class jdistlib.Nakagami
density(double, double, double, boolean) - Static method in class jdistlib.NegBinomial
density(double, double, double, boolean) - Static method in class jdistlib.NonCentralChiSquare
density(double, double, double, boolean) - Static method in class jdistlib.NonCentralT: From Johnson, Kotz and Balakrishnan (1995) [2nd ed.; formula (31.15), p.516], the non-central t density is f(x, df, ncp) = df^(df/2) * exp(-.5*ncp^2) / (sqrt(pi)*gamma(df/2)*(df+x^2)^((df+1)/2)) * sum_{k=0}^Inf gamma((df + k + df)/2)*ncp^k / prod(1:k)*(2*x^2/(df+x^2))^(k/2) The functional relationship f(x, df, ncp) = df/x * (F(sqrt((df+2)/df)*x, df+2, ncp) - F(x, df, ncp)) is used to evaluate the density at x != 0 and f(0, df, ncp) = exp(-.5*ncp^2) / (sqrt(pi)*sqrt(df)*gamma(df/2))*gamma((df+1)/2) is used for x=0.
density(double, double, double, boolean) - Static method in class jdistlib.Normal
density(double, double, double, boolean) - Static method in class jdistlib.PoissonInverseGaussian
density(double, double, double, boolean) - Static method in class jdistlib.PositiveNormal
density(double, double, double, boolean) - Static method in class jdistlib.Rice
density(double, double, double, boolean) - Static method in class jdistlib.Skellam
density(double, double, double, boolean) - Static method in class jdistlib.SkewedT
density(double, double, double, boolean) - Static method in class jdistlib.Slash
density(double, double, double, boolean) - Static method in class jdistlib.Uniform
density(double, double, double, boolean) - Static method in class jdistlib.Weibull
density(double, double, double, boolean) - Static method in class jdistlib.ZeroInflatedPoisson
density(double, double, double, boolean) - Static method in class jdistlib.ZeroTruncatedNegativeBinomial
density(double, double, double, double, boolean) - Static method in class jdistlib.AsymmetricLaplace
density(double, double, double, double, boolean) - Static method in class jdistlib.BetaBinomial: Density
density(double, double, double, double, boolean) - Static method in class jdistlib.BetaNegativeBinomial
density(double, double, double, double, boolean) - Static method in class jdistlib.BirnbaumSaunders
density(double, double, double, double, boolean) - Static method in class jdistlib.evd.Fretchet
density(double, double, double, double, boolean) - Static method in class jdistlib.evd.GeneralizedPareto
density(double, double, double, double, boolean) - Static method in class jdistlib.evd.GEV
density(double, double, double, double, boolean) - Static method in class jdistlib.evd.ReverseWeibull
density(double, double, double, double, boolean) - Static method in class jdistlib.ExponentiallyModifiedGaussian
density(double, double, double, double, boolean) - Static method in class jdistlib.GeneralizedGamma
density(double, double, double, double, boolean) - Static method in class jdistlib.Huber
density(double, double, double, double, boolean) - Static method in class jdistlib.HurdleNegativeBinomial
density(double, double, double, double, boolean) - Static method in class jdistlib.HyperGeometric
density(double, double, double, double, boolean) - Static method in class jdistlib.Makeham
density(double, double, double, double, boolean) - Static method in class jdistlib.NegativeHypergeometric
density(double, double, double, double, boolean) - Static method in class jdistlib.NonCentralBeta
density(double, double, double, double, boolean) - Static method in class jdistlib.NonCentralF
density(double, double, double, double, boolean) - Static method in class jdistlib.Triangular
density(double, double, double, double, boolean) - Static method in class jdistlib.Tukey
density(double, double, double, double, boolean) - Static method in class jdistlib.Tweedie: Tweedie density with mean mu, dispersion phi, and variance power xi.
density(double, double, double, double, boolean) - Static method in class jdistlib.ZeroInflatedNegativeBinomial
density(double, double, double, double, boolean, double) - Static method in class jdistlib.Tukey: Density of Tukey HSD distribution using differentials of the cumulative --- WARNING: Untested!
density(double, double, double, double, double, boolean) - Static method in class jdistlib.BivariatePoisson
density(double, double, double, double, double, boolean) - Static method in class jdistlib.FoldedNormal
density(double, double, double, double, double, boolean) - Static method in class jdistlib.GeneralizedBetaSecondKind
density(double, double, double, double, double, boolean) - Static method in class jdistlib.GeneralizedF
density(double, double, double, double, double, boolean) - Static method in class jdistlib.SinhArcsinh
density(double, double, double, double, double, boolean) - Static method in class jdistlib.Wiener
density(double, double, double, double, double, double, boolean) - Static method in class jdistlib.BivariateLogistic
density(double, double, double, double, double, double, boolean) - Static method in class jdistlib.FellerPareto
density(double, int) - Static method in class jdistlib.Kendall: Density of Kendall distribution
density(double, int) - Static method in class jdistlib.Spearman: Density.
density(double, GenericDistribution, int, boolean, boolean) - Static method in class jdistlib.evd.Extreme
density(double, GenericDistribution, int, int, boolean, boolean) - Static method in class jdistlib.evd.Order
density(int[], int[], int, boolean) - Static method in class jdistlib.MultivariateHypergeometric
density(int[], int, int) - Static method in class jdistlib.Ansari
density(int, boolean) - Method in class jdistlib.SignRank
density(int, boolean) - Method in class jdistlib.Wilcoxon
density(int, int, double, boolean) - Static method in class jdistlib.Zipf
density(int, int, int) - Static method in class jdistlib.Ansari
Density - Class in jdistlib.math.density: Corresponds to R's density function.
density_mu(double, double, double, boolean) - Static method in class jdistlib.NegBinomial
density_raw(double, double, boolean) - Static method in class jdistlib.Poisson
density_raw(double, double, double, double, boolean) - Static method in class jdistlib.Binomial
density_tau(double, int) - Static method in class jdistlib.Kendall: Density of Kendall distribution
densityAdaptive(TransformDistribution, double, FourierInversionOptions) - Static method in class jdistlib.finance.DistributionTransforms: Adaptive Fourier density inversion with explicit truncation/work controls.
densityFromCholesky(double[][], double, double[][], boolean) - Static method in class jdistlib.Wishart: Density overload accepting the lower Cholesky factor L of scale.
densityInto(double[], int, double[], int, int, boolean) - Method in class jdistlib.generic.GenericDistribution: Evaluates densities into caller-owned storage after one range validation.
densityResult(double) - Method in class jdistlib.finance.CgmyDistribution
densityResult(double) - Method in class jdistlib.finance.LevyIncrementDistribution
densityResult(double) - Method in class jdistlib.finance.MeixnerDistribution
densityResult(double) - Method in class jdistlib.finance.NormalTemperedStableDistribution
densityResult(double) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
dependencies() - Method in class jdistlib.inference.FactorSpec
derivatives(double, double[], double[], double[], double[]) - Method in interface jdistlib.inference.solver.OdeSystem: Writes the state derivative into derivative.
description() - Method in class jdistlib.accelerator.ComputeDeviceInfo
description() - Method in class jdistlib.accelerator.ComputeSelection
description() - Method in class jdistlib.accelerator.ExecutionPlan
description() - Method in interface jdistlib.inference.ParameterConstraint
detail - Variable in class jdistlib.math.IntegrationResult: Additional context supplied by the hardened API.
detailedMessage() - Method in class jdistlib.math.ImmutableIntegrationResult
detailedMessage() - Method in class jdistlib.math.IntegrationResult: Returns the status message with any hardened-API context appended.
determinantCumulative(double, double, double[][]) - Static method in class jdistlib.Wishart
determinantCumulative(double, double, double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.Wishart: Computes P(determinant(W) <= upper).
determinantProbability(double, double, double, double[][]) - Static method in class jdistlib.Wishart
determinantProbability(double, double, double, double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.Wishart: Computes P(lower <= determinant(W) <= upper).
determinantSign() - Method in class jdistlib.accelerator.FloatLuFactor
determinantSign() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
determinantSign() - Method in class jdistlib.accelerator.LuFactor
determinantSign() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
deviance(double, double, double) - Static method in class jdistlib.Tweedie
device() - Method in class jdistlib.accelerator.ComputeCapabilities
device() - Method in class jdistlib.accelerator.ComputeDeviceInfo
device() - Method in class jdistlib.accelerator.ComputeSelection
device() - Method in class jdistlib.accelerator.ExecutionPlan
deviceId() - Method in class jdistlib.accelerator.ComputeDeviceInfo
deviceInfo() - Method in interface jdistlib.accelerator.ComputeBackend: Returns stable backend, runtime, driver, and device provenance where available.
deviceInfo() - Method in class jdistlib.accelerator.ComputeSelection: Returns detailed runtime, driver, API, and device identification.
deviceInfo() - Method in class jdistlib.accelerator.CpuComputeBackend
df - Variable in class jdistlib.Chi
df - Variable in class jdistlib.ChiSquare
df - Variable in class jdistlib.NonCentralChiSquare
df - Variable in class jdistlib.NonCentralT
df - Variable in class jdistlib.SkewedT
df - Variable in class jdistlib.T
df - Variable in class jdistlib.Tukey
DF_MATCH - Enum constant in enum class jdistlib.math.spline.SmoothSplineCriterion
df1 - Variable in class jdistlib.F
df1 - Variable in class jdistlib.NonCentralF
df2 - Variable in class jdistlib.F
df2 - Variable in class jdistlib.NonCentralF
dgemm(MatrixTranspose, MatrixTranspose, int, int, int, double, double[], double[], double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dgemm(MatrixTranspose, MatrixTranspose, int, int, int, double, double[], int, int, double[], int, int, double, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend: Region-aware GEMM with row-major offsets and leading dimensions.
dgemmBatched(MatrixTranspose, MatrixTranspose, int, int, int, double, double[][], double[][], double, double[][]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dgemv(MatrixTranspose, int, int, double, double[], double[], double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dgemv(MatrixTranspose, int, int, double, double[], int, int, double[], int, int, double, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend: Region-aware GEMV with a row-major leading dimension and strided vectors.
dgeqp3(double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dger(int, int, double, double[], int, int, double[], int, int, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dgesvd(double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dgetrf(double[], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dgetrfBatched(double[][], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
diagnose(double[]) - Method in interface jdistlib.Copula: Classifies the point for safe CDF and density interpretation.
diagnose(double[]) - Method in class jdistlib.CopulaDistribution: Diagnoses the point after transformation through the marginal CDFs.
diagnose(double[]) - Method in class jdistlib.IndependenceCopula
DiagnosticFinding - Class in jdistlib: One evidence-based finding produced by a numerical distribution analyzer.
DiagnosticFinding(DiagnosticFinding.Severity, String, String) - Constructor for class jdistlib.DiagnosticFinding
DiagnosticFinding(DiagnosticFinding.Severity, String, String, double) - Constructor for class jdistlib.DiagnosticFinding
DiagnosticFinding.Severity - Enum Class in jdistlib
DiagnosticGraphs - Class in jdistlib.inference: Factories for trace, rank, autocorrelation, energy, and pair-plot datasets.
DiagnosticJson - Class in jdistlib: Dependency-free RFC 8259 serialization for numerical diagnostic reports.
diagnosticPreset(DiagnosticPreset) - Method in class jdistlib.NumericalContinuousDistribution.Builder
DiagnosticPreset - Enum Class in jdistlib: Balanced starting points for custom-kernel diagnostics.
diagnostics() - Method in class jdistlib.inference.Fit
diagnostics() - Method in class jdistlib.inference.HybridSamplingResult
diagnostics() - Method in exception class jdistlib.inference.lang.ModelScriptException
diagonal() - Static method in class jdistlib.inference.MetricConfiguration
diagonal(double[], double[]) - Static method in interface jdistlib.inference.GaussianReference: Independent Gaussian reference parameterized by marginal standard deviations.
DIAGONAL - Enum constant in enum class jdistlib.inference.MetricConfiguration.Type
diagonalBlocks() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
diagonalBlocks() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
diff(double[]) - Static method in class jdistlib.math.VectorMath
diff(double[], int) - Static method in class jdistlib.math.VectorMath
diff(double[], int, int) - Static method in class jdistlib.math.VectorMath
differenceFromBest() - Method in class jdistlib.inference.LooModelComparison.Entry
differenceStandardError() - Method in class jdistlib.inference.LooModelComparison.Entry
differenceStep - Variable in class jdistlib.inference.solver.AlgebraicSolver.Options
DifferentiableLogDensity - Interface in jdistlib.inference: A log density capable of adding its gradient to caller-owned storage.
DifferentiableModelFactor - Interface in jdistlib.inference: A factor that adds derivatives with respect to all constrained coordinates.
differentiate() - Method in class jdistlib.math.Polynomial: Compute the derivative of this polynomial and store the result into a new instance of QPolynomial
digamma(double) - Static method in class jdistlib.math.PolyGamma
digamma(double[]) - Static method in class jdistlib.math.PolyGamma
dimension() - Method in class jdistlib.accelerator.CholeskyFactor: Returns the matrix dimension.
dimension() - Method in class jdistlib.accelerator.FloatCholeskyFactor
dimension() - Method in class jdistlib.accelerator.FloatLuFactor
dimension() - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
dimension() - Method in class jdistlib.accelerator.FloatSymmetricEigenDecomposition
dimension() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
dimension() - Method in class jdistlib.accelerator.LuFactor
dimension() - Method in interface jdistlib.accelerator.PreparedCholesky
dimension() - Method in interface jdistlib.accelerator.PreparedFloatCholesky
dimension() - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
dimension() - Method in interface jdistlib.accelerator.PreparedSparseCholesky
dimension() - Method in class jdistlib.accelerator.SparseCholeskyFactor
dimension() - Method in class jdistlib.accelerator.SymmetricEigenDecomposition
dimension() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
dimension() - Method in class jdistlib.BB1Copula
dimension() - Method in class jdistlib.ClaytonCopula
dimension() - Method in interface jdistlib.Copula: Number of coordinates.
dimension() - Method in class jdistlib.CopulaDistribution
dimension() - Method in class jdistlib.CVineCopula
dimension() - Method in class jdistlib.DVineCopula
dimension() - Method in class jdistlib.finance.MultivariateFinancialDistribution
dimension() - Method in class jdistlib.FrankCopula
dimension() - Method in class jdistlib.GaussianCopula
dimension() - Method in class jdistlib.GumbelCopula
dimension() - Method in class jdistlib.IndependenceCopula
dimension() - Method in class jdistlib.inference.autodiff.ReverseModeLogDensity
dimension() - Method in class jdistlib.inference.BayesianModel
dimension() - Method in class jdistlib.inference.ChainResult
dimension() - Method in class jdistlib.inference.MixedStateSpace
dimension() - Method in class jdistlib.inference.ReversibleJumpModelSpace
dimension() - Method in class jdistlib.inference.ReversibleJumpState
dimension() - Method in class jdistlib.JoeCopula
dimension() - Method in class jdistlib.MixedCopulaDistribution
dimension() - Method in class jdistlib.RotatedCopula
dimension() - Method in class jdistlib.StudentTCopula
DimensionMatchingResult - Class in jdistlib.inference: One side of a dimension-matching map: state plus complementary auxiliaries.
DimensionMatchingResult(ReversibleJumpState, double...) - Constructor for class jdistlib.inference.DimensionMatchingResult
DimensionMatchingTransformation - Interface in jdistlib.inference: Reversible mapping between parameter/auxiliary pairs of equal total dimension.
DimensionMatchingValidator - Class in jdistlib.inference: Executable round-trip, dimension, and reciprocal-Jacobian validation for RJ maps.
dimensions() - Method in interface jdistlib.accelerator.PreparedLogisticRegression
dimensions() - Method in class jdistlib.inference.AcceleratedLogisticRegression
diptest(double[]) - Static method in class jdistlib.disttest.DistributionTest: Perform Hartigan's dip test, assuming the minimum test statistics D is zero.
diptest_presorted(double[]) - Static method in class jdistlib.disttest.DistributionTest: Perform Hartigan's dip test, assuming the minimum test statistics D is zero.
Dirichlet - Class in jdistlib: Dirichlet distribution on a probability simplex.
DirichletMultinomial - Class in jdistlib: Dirichlet-multinomial (multivariate Pólya) distribution.
discontinuityRatio(double) - Method in class jdistlib.FunctionAnalysisOptions.Builder
discrete() - Method in class jdistlib.inference.CoordinateSupport
discrete(GenericDistribution) - Static method in class jdistlib.CopulaMarginal: Declares a discrete marginal, deriving F(x-) as F(x)-p(x).
discrete(GenericDistribution, DoubleUnaryOperator) - Static method in class jdistlib.CopulaMarginal: Declares a discrete marginal with an explicit left-limit CDF.
DISCRETE - Enum constant in enum class jdistlib.CopulaMarginal.Kind
discreteCoordinates() - Method in class jdistlib.inference.MixedStateSpace
DiscreteFdr - Class in jdistlib.disttest: FDR procedures that exploit known heterogeneous discrete null CDFs.
DiscreteFdr.Result - Class in jdistlib.disttest: Rejection decisions and level-dependent DBH critical values.
DiscreteLaplace - Class in jdistlib: Discrete Laplace distribution on the lattice location + Z.
DiscreteLaplace(double, double) - Constructor for class jdistlib.DiscreteLaplace
DiscreteMetropolisKernel - Class in jdistlib.inference: Symmetric Metropolis update for one bounded or unbounded discrete coordinate.
DiscreteMetropolisKernel(int) - Constructor for class jdistlib.inference.DiscreteMetropolisKernel
DiscretePValueDistribution - Class in jdistlib.disttest: Finite null distribution of a discrete p-value.
DiscretePValueDistribution(double[], double[]) - Constructor for class jdistlib.disttest.DiscretePValueDistribution
DiscreteTailBound - Interface in jdistlib: User-supplied certificate bounding all unnormalized mass beginning at an omitted integer.
DiscreteTailBounds - Class in jdistlib: Factory methods for common caller-certified infinite-series tail bounds.
DiscreteWeibull - Class in jdistlib: Nakagawa-Osaki type-I discrete Weibull distribution on nonnegative integers.
DiscreteWeibull(double, double) - Constructor for class jdistlib.DiscreteWeibull
dist - Variable in class jdistlib.evd.Extreme
dist - Variable in class jdistlib.evd.Order
distance(double[]) - Static method in class jdistlib.math.VectorMath: Euclidian distance / Root mean square
distortedExpectation(GenericDistribution, RiskConvention, AdvancedRiskMeasures.Distortion) - Static method in class jdistlib.finance.AdvancedRiskMeasures: Choquet expectation integral Q(p) d g(p), with endpoint-preserving distortion g.
distribution(double[]) - Method in interface jdistlib.finance.DistributionFit.ParametricFamily
distribution(double[]) - Method in interface jdistlib.finance.OptionInference.DrawDistribution
DistributionAggregation - Class in jdistlib.finance: Reproducible aggregation, product/ratio, compound-sum, and scenario helpers.
DistributionAggregation.ScenarioTransformation - Interface in jdistlib.finance
DistributionAnalysis - Class in jdistlib: Numerical self-consistency checks for a constructed distribution.
DistributionApproximation - Class in jdistlib.finance: An approximate composed law together with strategy, error, and seed provenance.
DistributionApproximation(GenericDistribution, NumericalEstimate, long) - Constructor for class jdistlib.finance.DistributionApproximation
DistributionFit - Class in jdistlib.finance: Bounded MLE/MAP fitting with censored and interval observations.
DistributionFit.CalibrationLoss - Interface in jdistlib.finance
DistributionFit.LogPrior - Interface in jdistlib.finance
DistributionFit.Observation - Class in jdistlib.finance
DistributionFit.Observation.Kind - Enum Class in jdistlib.finance
DistributionFit.ParametricFamily - Interface in jdistlib.finance
DistributionFit.Result - Class in jdistlib.finance
Distributions - Class in jdistlib: Concise factories for composing scalar distribution objects.
DistributionTest - Class in jdistlib.disttest: Comparing two distributions
DistributionTest() - Constructor for class jdistlib.disttest.DistributionTest
DistributionTransforms - Class in jdistlib.finance: Numerical transform, cumulant, Fourier-inversion, and Esscher-tilt helpers.
DistributionTransforms.TiltResult - Class in jdistlib.finance: Result retaining the tilted law and its normalization diagnostics.
DivergenceLocation - Class in jdistlib.inference: Location and energy error for one divergent retained transition.
divergences() - Method in class jdistlib.inference.SamplerDiagnostics
Divergences - Class in jdistlib.inference: Extracts sampler pathologies with coordinates suitable for plotting.
divergent() - Method in class jdistlib.inference.ColumnarDraws
divergent() - Method in class jdistlib.inference.IterationStats
divide(int, double) - Method in class jdistlib.inference.autodiff.ReverseTape
divide(int, int) - Method in class jdistlib.inference.autodiff.ReverseTape
divide(Complex) - Method in class jdistlib.math.Complex
dlogfdphi(double, double, double, double) - Static method in class jdistlib.Tweedie: Calculates d(log f)/d(phi) for the Tweedie densities.
dnrm2(int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dot(double[], double[]) - Method in interface jdistlib.accelerator.ComputeBackend
dot(double[], double[]) - Method in class jdistlib.accelerator.CpuComputeBackend
dot(double[], double[]) - Static method in class jdistlib.math.VectorMath: Weighted sum / Dot product
dot(double[], int[]) - Static method in class jdistlib.math.VectorMath: Weighted sum / Dot product
dot(int[], double[]) - Static method in class jdistlib.math.VectorMath: Weighted sum / Dot product
dot(int[], int[]) - Static method in class jdistlib.math.VectorMath: Weighted sum / Dot product
DOT - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
DOUBLE_EXPONENTIAL - Enum constant in enum class jdistlib.math.IntegrationOptions.Method: Double-exponential tanh-sinh, exp-sinh, or sinh-sinh quadrature, selected according to the interval bounds.
doublePrecision() - Method in class jdistlib.accelerator.ComputeCapabilities
downsideDeviation(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk
dpbfa(double[][], int) - Static method in class jdistlib.math.LinPack: dpbfa factors a double precision symmetric positive definite matrix stored in band form.
dpbsl(double[][], int, double[]) - Static method in class jdistlib.math.LinPack: dpbsl solves the double precision symmetric positive definite band system a*x = b using the factors computed by dpbco or dpbfa.
dpotrf(double[], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dpotrfBatched(double[][], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dpsifn(double, int, int, int) - Static method in class jdistlib.math.PolyGamma
draw() - Method in class jdistlib.inference.DivergenceLocation
draw(int) - Method in class jdistlib.inference.ReversibleJumpResult
draw(int) - Method in class jdistlib.inference.SparseSubsetResult
draws() - Method in class jdistlib.inference.PathfinderFit
draws() - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
draws() - Method in class jdistlib.inference.ReversibleJumpParameterSummary
draws() - Method in class jdistlib.inference.ReversibleJumpResult
draws() - Method in class jdistlib.inference.SparseSubsetResult
drawsForModel(long) - Method in class jdistlib.inference.ReversibleJumpResult: Returns rectangular parameters for draws in one model, preserving retained order.
drawSink(DrawSink) - Method in class jdistlib.inference.SamplingOptions.Builder
drawSink(ReversibleJumpDrawSink) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
drawSink(SparseSubsetDrawSink) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
DrawSink - Interface in jdistlib.inference: Streaming destination for retained draws; implementations must copy if needed later.
drawsPerChain() - Method in class jdistlib.inference.McmcDiagnosticReport
drawsPerPath() - Method in class jdistlib.inference.PathfinderOptions
drawsPerPath(int) - Method in class jdistlib.inference.PathfinderOptions.Builder
driverVersion() - Method in class jdistlib.accelerator.ComputeDeviceInfo
dscal(int, double, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dswap(int, double[], int, int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsyev(double[], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsygvd(double[], double[], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsymm(MatrixSide, MatrixTriangle, int, int, double, double[], double[], double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsyr(MatrixTriangle, int, double, double[], int, int, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsyr2(MatrixTriangle, int, double, double[], int, int, double[], int, int, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsyr2k(MatrixTriangle, MatrixTranspose, int, int, double, double[], double[], double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsyrk(MatrixTranspose, int, int, double, double[], double, double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsyrk(MatrixTranspose, int, int, double, double[], int, int, double, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dsytrf(double[], int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dtrsm(MatrixSide, MatrixTriangle, MatrixTranspose, MatrixDiagonal, int, int, double, double[], double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dtrsm(MatrixSide, MatrixTriangle, MatrixTranspose, MatrixDiagonal, int, int, double, double[], int, int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend: Region-aware triangular multi-right-side solve.
dtrsv(MatrixTriangle, MatrixTranspose, MatrixDiagonal, int, double[], double[]) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
dtweedie_saddle(double, double, double, double, double, boolean) - Static method in class jdistlib.Tweedie
dtweedie_series(double, double, double, double, boolean) - Static method in class jdistlib.Tweedie
dualAveragingState() - Method in class jdistlib.inference.SamplerCheckpoint
DVineCopula - Class in jdistlib: Simplified D-vine copula assembled from bivariate conditional copulas.
DVineCopula(PairCopula[]...) - Constructor for class jdistlib.DVineCopula: Creates a D-vine.
dynamicRangeOrders(double) - Method in class jdistlib.FunctionAnalysisOptions.Builder

E

ebd0(double, double, double[]) - Static method in class jdistlib.math.MathFunctions: Computes the deviance part x * log(x / mean) + mean - x as a high and low component.
edges() - Method in class jdistlib.inference.ModelGraph
effectiveNumberOfParameters() - Method in class jdistlib.inference.PsisLoo.Result
effectiveNumberOfParameters() - Method in class jdistlib.inference.Waic.Result
effectiveSampleSize() - Method in class jdistlib.inference.PsisLoo.Result
effectiveSampleSize(double[]) - Static method in class jdistlib.inference.MonteCarloError
eigenvalues() - Method in class jdistlib.accelerator.FloatSymmetricEigenDecomposition: Returns eigenvalues in ascending order.
eigenvalues() - Method in class jdistlib.accelerator.SymmetricEigenDecomposition: Returns eigenvalues in ascending order.
eigenvectors() - Method in class jdistlib.accelerator.FloatSymmetricEigenDecomposition: Returns a row-major orthogonal matrix whose columns are eigenvectors.
eigenvectors() - Method in class jdistlib.accelerator.SymmetricEigenDecomposition: Returns a row-major orthogonal matrix whose columns are eigenvectors.
elapsedNanoseconds() - Method in class jdistlib.inference.FactorProfile
elapsedNanoseconds() - Method in class jdistlib.inference.RunManifest
EllipticalSliceSampler - Class in jdistlib.inference: Tuning-free elliptical slice sampler; target is the likelihood-only log density.
EllipticalSliceSampler(GaussianReference) - Constructor for class jdistlib.inference.EllipticalSliceSampler
elpd() - Method in class jdistlib.inference.LooModelComparison.Entry
elpd() - Method in class jdistlib.inference.PsisLoo.Result
elpd() - Method in class jdistlib.inference.Waic.Result
elpd(int, String) - Method in interface jdistlib.inference.PsisLoo.ExactLooFallback
Empirical - Class in jdistlib: Discrete empirical distribution that samples observations with replacement.
Empirical(double[]) - Constructor for class jdistlib.Empirical
EmpiricalDistribution - Class in jdistlib.finance: Immutable equal-weight empirical distribution used by reproducible fallbacks.
EmpiricalDistribution(double[]) - Constructor for class jdistlib.finance.EmpiricalDistribution
empty() - Static method in class jdistlib.inference.lang.ExternalFunctionRegistry
empty() - Static method in class jdistlib.math.CallbackProfile: Empty profile used by legacy integration overloads.
endsSlowWindow(int) - Method in class jdistlib.inference.WarmupSchedule.Resolved
energy() - Method in class jdistlib.inference.IterationStats
energy(int, ChainResult...) - Static method in class jdistlib.inference.DiagnosticGraphs
energyBayesianFractionMissingInformation() - Method in class jdistlib.inference.SamplerDiagnostics
energyError() - Method in class jdistlib.inference.DivergenceLocation
energyError() - Method in class jdistlib.inference.IterationStats
entries() - Method in class jdistlib.inference.WarmupTrace
entropic(GenericDistribution, double, RiskConvention) - Static method in class jdistlib.finance.AdvancedRiskMeasures: Entropic risk log E exp(theta*loss)/theta with an explicit MGF-domain check.
entropy() - Method in class jdistlib.NumericalContinuousDistribution: Numerically evaluates differential entropy, -E[log f(X)].
entropy() - Method in class jdistlib.NumericalDiscreteDistribution: Shannon entropy in nats.
EPANECHNIKOV - Enum constant in enum class jdistlib.math.density.Kernel
equals(Object) - Method in class jdistlib.inference.lang.TupleValue
equals(Object) - Method in class jdistlib.inference.ObservationMetadata
equals(Object) - Method in class jdistlib.inference.ReversibleJumpState
equals(Object) - Method in class jdistlib.inference.SparseSubsetState
equals(Object) - Method in class jdistlib.math.Complex
equicoordinateQuantile(double, double[], double[][]) - Static method in class jdistlib.MultivariateCauchy
equicoordinateQuantile(double, double[], double[][]) - Static method in class jdistlib.MultivariateLogNormal
equicoordinateQuantile(double, double[], double[][]) - Static method in class jdistlib.MultivariateNormal
equicoordinateQuantile(double, double[], double[][], double) - Static method in class jdistlib.MultivariateStudentT
equicoordinateQuantile(double, double[], double[][], double, MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateStudentT: Equicoordinate quantile, with one common threshold in every dimension.
equicoordinateQuantile(double, double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateCauchy
equicoordinateQuantile(double, double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateLogNormal: Equicoordinate quantile on the original, positive measurement scale.
equicoordinateQuantile(double, double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateNormal: Finds the scalar q satisfying P[X[i] <= q for every i] = p.
erf__(double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF THE REAL ERROR FUNCTION -----------------------------------------------------------------------
erfc1(int, double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF THE COMPLEMENTARY ERROR FUNCTION ERFC1(IND,X) = ERFC(X) IF IND = 0 ERFC1(IND,X) = EXP(X*X)*ERFC(X) OTHERWISE -----------------------------------------------------------------------
ERROR - Enum constant in enum class jdistlib.DiagnosticFinding.Severity
ERROR - Enum constant in enum class jdistlib.inference.HealthSeverity
esscherTilt(GenericDistribution, double) - Static method in class jdistlib.finance.DistributionTransforms: Constructs a normalized exponentially tilted continuous distribution.
essPerEvaluation(double, long) - Static method in class jdistlib.inference.MonteCarloError
essPerSecond(double, long) - Static method in class jdistlib.inference.MonteCarloError
estimatedAllocatedBytes() - Method in class jdistlib.inference.FactorProfile: Best-effort positive heap-growth estimate; use a profiler for exact allocation attribution.
estimatedFalseDiscoveryRate(double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Estimates FDR at a raw p-value cutoff using the default spline pi-zero estimate.
estimatedFalseDiscoveryRate(double[], double, double) - Static method in class jdistlib.disttest.MultipleTesting: Estimates FDR at a raw cutoff for a caller-supplied pi-zero.
estimateNullProportion(double[]) - Static method in class jdistlib.disttest.MultipleTesting: Estimates pi-zero with the default lambda grid and three spline degrees of freedom.
estimateNullProportion(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Estimates the true-null proportion by smoothing the Storey estimates over lambda and predicting at the largest lambda.
estimateNullProportionQuantile(double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Uses the default lambda grid for the quantile pi-zero estimator.
estimateNullProportionQuantile(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Estimates pi-zero as a quantile of the estimates across lambda values.
esum(int, double, boolean) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF EXP(MU + X) -----------------------------------------------------------------------
eval(double) - Method in class jdistlib.math.approx.ApproximationFunction
eval(double) - Method in interface jdistlib.math.UnivariateFunction
eval(double...) - Method in interface jdistlib.math.MultivariableFunction
evaluate(double) - Method in class jdistlib.math.Polynomial: Evaluate this polynomial at x = x0
evaluate(double[]) - Method in interface jdistlib.inference.GeneratedQuantity
evaluate(double[]) - Method in class jdistlib.math.Polynomial: Evaluate this polynomial based on a precomputed vector of powers of the variable.
evaluate(double[][]) - Method in interface jdistlib.inference.lang.StanExternalFunction: Evaluates flattened arguments and returns values plus a complete Jacobian.
evaluate(double[][], double) - Method in interface jdistlib.accelerator.PreparedLogisticRegression
evaluate(double[], double[], double[], double[]) - Method in interface jdistlib.inference.solver.AlgebraicSystem: Writes the residual into residual.
evaluate(ReverseDifferentiableFunction, double[], double[]) - Method in class jdistlib.inference.autodiff.ReverseModeGradient: Evaluates the function and writes its gradient without allocating tape nodes.
evaluate(ReverseTape, int[]) - Method in interface jdistlib.inference.autodiff.ReverseDifferentiableFunction
evaluate(BayesianModel, double[], int...) - Method in class jdistlib.inference.ModelEvaluationCache
evaluate(ModelState) - Method in interface jdistlib.inference.PointwiseLogLikelihoodEvaluator
EVALUATION_BUDGET_EXCEEDED - Enum constant in enum class jdistlib.CopulaMeasureResult.Status
EVALUATION_BUDGET_EXHAUSTED - Enum constant in enum class jdistlib.math.IntegrationStatus
EvaluationCounter - Class in jdistlib.inference: Thread-confined log-density wrapper reporting value and gradient work.
EvaluationCounter(DifferentiableLogDensity) - Constructor for class jdistlib.inference.EvaluationCounter
evaluations - Variable in class jdistlib.MultivariateProbabilityResult: Number of transformed-integrand evaluations.
evaluations() - Method in class jdistlib.inference.OptimizationResult
evaluations() - Method in class jdistlib.inference.solver.AlgebraicSolver.Result
evaluator() - Method in class jdistlib.inference.BayesianModel
evidence() - Method in class jdistlib.inference.HealthIssue
exact(double) - Static method in class jdistlib.finance.DistributionFit.Observation
exact(double[]) - Static method in class jdistlib.disttest.DiscretePValueDistribution: Builds the common exact-p-value distribution with F(t)=t on its support.
exact(double, double) - Static method in class jdistlib.finance.DistributionFit.Observation
EXACT - Enum constant in enum class jdistlib.finance.DistributionFit.Observation.Kind
EXACT_CONTINUOUS - Enum constant in enum class jdistlib.CopulaMeasureResult.Status
exactDiscreteConvolution(GenericDistribution...) - Static method in class jdistlib.finance.DistributionAggregation: Exact convolution of finite integer-valued atom-aware distributions.
ExecutionKind - Enum Class in jdistlib.accelerator: How an inspected operation is expected to execute.
ExecutionPlan - Class in jdistlib.accelerator: Immutable prediction of where and how one operation will execute.
ExecutionPlan(LinearAlgebraOperation, NumericPrecision, ExecutionKind, String, String, String) - Constructor for class jdistlib.accelerator.ExecutionPlan
exp() - Method in class jdistlib.math.Complex
exp(int) - Method in class jdistlib.inference.autodiff.ReverseTape
EXP - Enum constant in enum class jdistlib.accelerator.UnaryOperation
exparg(int) - Static method in class jdistlib.math.MathFunctions: --------------------------------------------------------------------
expectation(UnivariateFunction) - Method in class jdistlib.NumericalContinuousDistribution: Numerically evaluates E[g(X)] with immutable integration diagnostics.
expectation(UnivariateFunction) - Method in class jdistlib.NumericalDiscreteDistribution: Exactly evaluates E[g(X)] over the retained finite support.
expectedShortfall(double, RiskConvention) - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
expectedShortfall(GenericDistribution, double, RiskConvention) - Static method in class jdistlib.finance.FinancialRisk: Atom-aware expected loss beyond VaR, defined through the quantile integral.
expectedShortfallMagnitude(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk
expectile(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk: Asymmetric least-squares expectile with a bracket/convergence report.
expm1(int) - Method in class jdistlib.inference.autodiff.ReverseTape
Exponential - Class in jdistlib
Exponential(double) - Constructor for class jdistlib.Exponential
ExponentiallyModifiedGaussian - Class in jdistlib: Distribution of an independent normal variate plus an exponential variate.
ExponentiallyModifiedGaussian(double, double, double) - Constructor for class jdistlib.ExponentiallyModifiedGaussian
ExternalFunctionRegistry - Class in jdistlib.inference.lang: Immutable name-to-Java registry for forward-declared Stan functions.
ExternalFunctionRegistry.Builder - Class in jdistlib.inference.lang
ExternalFunctionResult - Class in jdistlib.inference.lang: Immutable external-function values and derivatives with respect to flattened arguments.
ExternalFunctionResult(double[], int[], double[][]) - Constructor for class jdistlib.inference.lang.ExternalFunctionResult
extract(PointwiseLogLikelihood, ChainResult...) - Static method in class jdistlib.inference.PointwiseLogLikelihoodDraws
extractPointwiseLogLikelihood(ChainResult...) - Method in interface jdistlib.inference.PointwiseLogLikelihood
EXTRAPOLATION_ROUNDOFF - Enum constant in enum class jdistlib.math.IntegrationStatus
Extreme - Class in jdistlib.evd: Extreme distribution.
Extreme(GenericDistribution, int, boolean) - Constructor for class jdistlib.evd.Extreme
ExtremeValueInference - Class in jdistlib.finance: GEV/GPD fitting, tail-index estimators, return levels, and threshold diagnostics.
ExtremeValueInference.ThresholdDiagnostics - Class in jdistlib.finance

F

f - Variable in class jdistlib.math.IntegrationResult
F - Class in jdistlib
F(double, double) - Constructor for class jdistlib.F
factor() - Method in class jdistlib.inference.FactorSpec
factor(String, String[], ModelFactor) - Method in class jdistlib.inference.ModelBuilder
FACTOR - Enum constant in enum class jdistlib.inference.ModelGraph.NodeKind
factorNonzeroCount() - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
factorNonzeroCount() - Method in interface jdistlib.accelerator.PreparedSparseCholesky: Number of entries in the current lower Cholesky factor.
FactorProfile - Class in jdistlib.inference: Immutable factor timing and numerical-stability snapshot.
FactorProfiler - Class in jdistlib.inference: Wraps factors without changing whether analytic gradients are available.
factors() - Method in class jdistlib.inference.BayesianModel
FactorSpec - Class in jdistlib.inference: Immutable factor metadata and evaluator.
factory() - Method in class jdistlib.inference.lang.LoadedGeneratedModel
failureX - Variable in class jdistlib.math.IntegrationResult: Coordinate associated with a callback or non-finite-value failure.
fallbackUsed() - Method in class jdistlib.inference.PsisLoo.Result
FALSE - Enum constant in enum class jdistlib.util.Bool3
FAST - Enum constant in enum class jdistlib.DiagnosticPreset
FellerPareto - Class in jdistlib: Five-parameter Feller-Pareto distribution from actuar.
FellerPareto(double, double, double, double, double) - Constructor for class jdistlib.FellerPareto
fftConvolution(double[], double, double[], double, double) - Static method in class jdistlib.finance.DistributionAggregation: Linear (non-cyclic) FFT convolution of two equal-step probability grids.
FINAL_FAST - Enum constant in enum class jdistlib.inference.WarmupSchedule.Phase
finalStepSize() - Method in class jdistlib.inference.WarmupResult
FinancialRisk - Class in jdistlib.finance: Atom-aware tail-risk, partial-moment, and option-payoff functionals.
findRoots() - Method in class jdistlib.math.Polynomial: Returns the root.
findRoots(double[], double[]) - Static method in class jdistlib.math.Polynomial: Jenkins-Traub algorithm for finding root of polynomials.
findScalarQuotient(Polynomial) - Method in class jdistlib.math.Polynomial
finite() - Method in class jdistlib.inference.CoordinateSupport
finiteDifference(LogDensity) - Static method in class jdistlib.inference.Gradients: Creates a central finite-difference adapter for diagnostic or fallback use.
finiteDifference(LogDensity, double) - Static method in class jdistlib.inference.Gradients
FiniteDiscreteGibbsKernel - Class in jdistlib.inference: Exact full-conditional update for one finite integer or categorical coordinate.
FiniteDiscreteGibbsKernel(int) - Constructor for class jdistlib.inference.FiniteDiscreteGibbsKernel
FiniteGridDistribution - Class in jdistlib.finance: Immutable equally-spaced finite distribution used by exact/FFT/Panjer grids.
FiniteGridDistribution(double, double, double[]) - Constructor for class jdistlib.finance.FiniteGridDistribution
fit(double[][], CopulaFamily) - Static method in class jdistlib.CopulaFitter
fit(double[][], CopulaFamily, CopulaFitOptions) - Static method in class jdistlib.CopulaFitter: Fits raw observations after applying marginal ranks.
fit(double[][], VineStructure) - Static method in class jdistlib.VineFitter
fit(double[], double[]) - Static method in class jdistlib.math.spline.SmoothSpline
fit(double[], double[], double[]) - Static method in class jdistlib.math.spline.SmoothSpline
fit(double[], double[], double[], SmoothSplineCriterion, double, double) - Static method in class jdistlib.math.spline.SmoothSpline
fit(double[], double[], double[], SmoothSplineCriterion, double, double, double) - Static method in class jdistlib.math.spline.SmoothSpline: Fit a smooth spline
fit(double[], double[], double[], SmoothSplineCriterion, double, double, double, double, double, double, int) - Static method in class jdistlib.math.spline.SmoothSpline: Fit a smooth spline
fit(double, double, OptionObservation[], OptionCalibration.Family, double[], int) - Static method in class jdistlib.finance.OptionCalibration
fit(String[], double[][]) - Static method in class jdistlib.inference.PredictiveStacking
fit(String[], PsisLoo.Result...) - Static method in class jdistlib.inference.PredictiveStacking
fit(DistributionFit.Observation[], DistributionFit.ParametricFamily, double[], DistributionFit.LogPrior, DistributionFit.CalibrationLoss, int, double) - Static method in class jdistlib.finance.DistributionFit
fit(DifferentiableLogDensity, double[][], PathfinderOptions, RandomEngine) - Static method in class jdistlib.inference.Pathfinder
fit(Sampler, LogDensity, double[][], SamplingOptions, long, int) - Static method in class jdistlib.inference.Inference
fit(Sampler, LogDensity, String, double[][], SamplingOptions, long, int) - Static method in class jdistlib.inference.Inference: Fits with a stable caller-provided model/source identity included in the manifest hash.
Fit - Class in jdistlib.inference: First-class inference result combining chains, diagnostics, and provenance.
fitDFMatch(double[], double[], double) - Static method in class jdistlib.math.spline.SmoothSpline
fitDFMatch(double[], double[], double[], double) - Static method in class jdistlib.math.spline.SmoothSpline
fitGev(double[]) - Static method in class jdistlib.finance.ExtremeValueInference
fitGevPwm(double[]) - Static method in class jdistlib.finance.ExtremeValueInference: Probability-weighted-moment initialization returned through the common result contract.
fitGpd(double[], double) - Static method in class jdistlib.finance.ExtremeValueInference
fitMixed(double[][], CopulaMarginal[], long, CopulaFamily) - Static method in class jdistlib.CopulaFitter: Fits declared marginals using a reproducible randomized transform.
fitMixed(double[][], CopulaMarginal[], long, CopulaFamily, CopulaFitOptions) - Static method in class jdistlib.CopulaFitter: Fits declared marginals using a reproducible randomized transform.
fitMixed(double[][], CopulaMarginal[], long, VineStructure, CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.VineFitter: Fits a vine after a reproducible randomized marginal transform.
fitMixed(double[][], CopulaMarginal[], CopulaFamily) - Static method in class jdistlib.CopulaFitter: Fits declared continuous/discrete marginals using midpoint transforms.
fitMixed(double[][], CopulaMarginal[], RandomEngine, CopulaFamily, CopulaFitOptions) - Static method in class jdistlib.CopulaFitter: Fits declared marginals using midpoint or randomized distributional transforms.
fitMixed(double[][], CopulaMarginal[], RandomEngine, VineStructure, CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.VineFitter: Fits a vine after continuous/discrete marginal probability transforms.
fitMixed(double[][], CopulaMarginal[], VineStructure, CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.VineFitter: Fits a vine after continuous/discrete marginal probability transforms.
fitUniforms(double[][], CopulaFamily) - Static method in class jdistlib.CopulaFitter
fitUniforms(double[][], CopulaFamily, CopulaFitOptions) - Static method in class jdistlib.CopulaFitter: Fits observations already transformed to the open unit hypercube.
fitUniforms(double[][], VineStructure, CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.VineFitter
FixedDimensionSamplerRjKernel - Class in jdistlib.inference: Adapts one frozen ordinary JDistlib sampler transition for use within an RJ model.
FixedDimensionSamplerRjKernel(String, Sampler, SamplingOptions) - Constructor for class jdistlib.inference.FixedDimensionSamplerRjKernel
fixedModelTarget(long) - Method in interface jdistlib.inference.ReversibleJumpTarget: Fixed-model view used to reuse ordinary JDistlib kernels; override to preserve analytic gradients.
fligner_test(double[], int[]) - Static method in class jdistlib.disttest.DistributionTest: Fligner-Killeen test
fligner_test(double[], int[], double) - Static method in class jdistlib.disttest.DistributionTest: Fligner-Killeen test with a significant-digits control for ranking centered absolute deviations.
FloatCholeskyFactor - Class in jdistlib.accelerator: Immutable FP32 lower Cholesky factor with reusable SPD solves.
FloatCholeskyFactor(int, float[]) - Constructor for class jdistlib.accelerator.FloatCholeskyFactor: Creates a factor from a row-major lower-triangular matrix.
FloatCsrMatrix - Class in jdistlib.matrix: Immutable FP32 CSR matrix with one-based Stan-compatible indices.
FloatCsrMatrix(int, int, float[], int[], int[]) - Constructor for class jdistlib.matrix.FloatCsrMatrix
FloatLuFactor - Class in jdistlib.accelerator: Immutable FP32 partial-pivoted LU factorization of a square matrix.
FloatLuFactor(int, float[], int[], int) - Constructor for class jdistlib.accelerator.FloatLuFactor
FloatPivotedQrFactor - Class in jdistlib.accelerator: Immutable FP32 column-pivoted Householder QR factorization.
FloatPivotedQrFactor(int, int, float[], float[], int[]) - Constructor for class jdistlib.accelerator.FloatPivotedQrFactor: Creates a factor from packed Householder QR storage and a zero-based pivot.
FloatSingularValueDecomposition - Class in jdistlib.accelerator: Immutable FP32 thin singular-value decomposition A = U*S*Vt.
FloatSingularValueDecomposition(int, int, float[], float[], float[]) - Constructor for class jdistlib.accelerator.FloatSingularValueDecomposition: Creates a thin SVD with descending singular values.
FloatSparseCholeskyFactor - Class in jdistlib.accelerator: Immutable FP32 sparse Cholesky factor with reusable solves.
FloatSymmetricEigenDecomposition - Class in jdistlib.accelerator: Immutable FP32 eigendecomposition of a real symmetric matrix.
FloatSymmetricEigenDecomposition(int, float[], float[]) - Constructor for class jdistlib.accelerator.FloatSymmetricEigenDecomposition: Creates a decomposition with ascending eigenvalues and eigenvectors in columns.
FloatSymmetricIndefiniteFactor - Class in jdistlib.accelerator: FP32 pivoted P*A*P' = L*D*L' factorization with 1x1/2x2 D blocks.
FloatSymmetricIndefiniteFactor(int, float[], float[], int[], int[]) - Constructor for class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
FLT_DIG - Static variable in class jdistlib.math.Constants
FLT_EPSILON - Static variable in class jdistlib.math.Constants
FLT_MANT_DIG - Static variable in class jdistlib.math.Constants
FLT_MAX_EXP - Static variable in class jdistlib.math.Constants
FLT_MIN_EXP - Static variable in class jdistlib.math.Constants
FLT_RADIX - Static variable in class jdistlib.math.Constants
fm - Variable in class jdistlib.Binomial.RandomState
FoldedNormal - Class in jdistlib: VGAM folded normal distribution, including asymmetric positive and negative scaling factors a1 and a2.
FoldedNormal(double, double) - Constructor for class jdistlib.FoldedNormal
FoldedNormal(double, double, double, double) - Constructor for class jdistlib.FoldedNormal
force() - Method in class jdistlib.inference.MappedDrawStore
FORCE - Enum constant in enum class jdistlib.inference.ComputeNuts: Require hardware-accelerated target evaluation even when it may be slower.
forNuts(SamplingOptions, double[][], double[], double) - Static method in class jdistlib.inference.AcceleratedLogisticRegression: Selects the backend from general sampling options for a NUTS workflow.
forPreset(DiagnosticPreset) - Static method in class jdistlib.FunctionAnalysisOptions: Returns the ready-to-use settings represented by a named preset.
forward(ReversibleJumpState, double[]) - Method in class jdistlib.inference.CoordinateInsertionTransformation
forward(ReversibleJumpState, double[]) - Method in class jdistlib.inference.CoordinateSplitTransformation
forward(ReversibleJumpState, double[]) - Method in interface jdistlib.inference.DimensionMatchingTransformation
FourierInversionOptions - Class in jdistlib.finance: Work, truncation, and convergence controls for adaptive Fourier inversion.
FP32 - Enum constant in enum class jdistlib.accelerator.NumericPrecision
FP64 - Enum constant in enum class jdistlib.accelerator.NumericPrecision
fpser(double, double, double, double, boolean) - Static method in class jdistlib.math.MathFunctions
FRANK - Enum constant in enum class jdistlib.CopulaFamily
FrankCopula - Class in jdistlib: Exchangeable Frank copula.
FrankCopula(int, double) - Constructor for class jdistlib.FrankCopula
freezeAdaptation() - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
freezeAdaptation() - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
freezeAdaptation() - Method in class jdistlib.inference.ModelSpecificRjKernel
freezeAdaptation() - Method in interface jdistlib.inference.ReversibleJumpMove
freezeAdaptation() - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
freezeAdaptation() - Method in interface jdistlib.inference.RjBirthProposal
freezeAdaptation() - Method in class jdistlib.inference.SubsetBirthMove
freezeAdaptation() - Method in class jdistlib.inference.SubsetDeathMove
freezeAdaptation() - Method in class jdistlib.inference.SubsetSwapMove
Fretchet - Class in jdistlib.evd: Fretchet distribution.
Fretchet(double, double, double) - Constructor for class jdistlib.evd.Fretchet
frexp(double, int[]) - Static method in class jdistlib.math.MathFunctions: Implementation of frexp
from() - Method in class jdistlib.inference.ModelGraph.Edge
from(WarmupResult, String, String) - Static method in class jdistlib.inference.WarmupBundle
fromCode(int) - Static method in enum class jdistlib.math.IntegrationStatus: Returns the typed status corresponding to a legacy integer code.
fromDense(int, int, double[], double) - Static method in class jdistlib.matrix.CsrMatrix: Converts a row-major dense matrix, omitting entries with absolute value at most tolerance.
fromKendallsTau(double[][]) - Static method in class jdistlib.GaussianCopula: Constructs the Gaussian copula whose pairwise Kendall tau matrix is supplied.
fromKendallsTau(double[][], double) - Static method in class jdistlib.StudentTCopula
fromKendallsTau(int, double) - Static method in class jdistlib.ClaytonCopula
fromKendallsTau(int, double) - Static method in class jdistlib.FrankCopula
fromKendallsTau(int, double) - Static method in class jdistlib.GumbelCopula
fromLogKernel(UnivariateFunction, double, double) - Static method in class jdistlib.NumericalContinuousDistribution: Constructs from a log-kernel, automatically selecting a finite reference value from deterministic interior probes.
fromLogKernel(UnivariateFunction, double, double, double, IntegrationOptions) - Static method in class jdistlib.NumericalContinuousDistribution: Constructs from a log-kernel with a user-supplied finite scaling reference.
fromLogKernel(UnivariateFunction, double, double, IntegrationOptions) - Static method in class jdistlib.NumericalContinuousDistribution: Constructs from a log-kernel with explicit integration options.
fromLogKernel(UnivariateFunction, NumericalSupport, UnivariateFunction, IntegrationOptions) - Static method in class jdistlib.NumericalPiecewiseDistribution: Constructs a regionally scaled piecewise distribution from log formulas.
fromLogWeights(UnivariateFunction, double[]) - Static method in class jdistlib.NumericalDiscreteDistribution: Constructs over explicit outcomes from unnormalized log-weights.
fromLogWeights(UnivariateFunction, int, int) - Static method in class jdistlib.NumericalDiscreteDistribution: Constructs over an inclusive integer range from unnormalized log-weights.
fromModel() - Method in class jdistlib.inference.ReversibleJumpIterationStats
fromS0(double, double, double, double) - Static method in class jdistlib.finance.StableDistribution: Converts Nolan S0 location to this class's canonical S1 location.
fromSize() - Method in class jdistlib.inference.SparseSubsetIterationStats
FunctionAnalysis - Class in jdistlib: Evidence gathered while probing and repeatedly integrating a kernel.
FunctionAnalysisOptions - Class in jdistlib: Immutable settings for probability-kernel sanity analysis.
FunctionAnalysisOptions.Builder - Class in jdistlib
functionEss(double[][], ToDoubleFunction<double[]>) - Static method in class jdistlib.inference.MonteCarloError
functionMcse(double[][], ToDoubleFunction<double[]>) - Static method in class jdistlib.inference.MonteCarloError

G

gam1(double) - Static method in class jdistlib.math.MathFunctions: ------------------------------------------------------------------ COMPUTATION OF 1/GAMMA(A+1) - 1 FOR -0.5 <= A <= 1.5 ------------------------------------------------------------------
gamln(double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- Evaluation of ln(gamma(a)) for positive a ----------------------------------------------------------------------- Written by Alfred H.
gamln1(double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF LN(GAMMA(1 + A)) FOR -0.2 <= A <= 1.25 -----------------------------------------------------------------------
gamma - Variable in class jdistlib.SkewedT
Gamma - Class in jdistlib
Gamma(double, double) - Constructor for class jdistlib.Gamma
gamma_cody(double) - Static method in class jdistlib.math.MathFunctions: ---------------------------------------------------------------------- This routine calculates the GAMMA function for a float argument X.
gammafn(double) - Static method in class jdistlib.math.MathFunctions
gammafn(double[]) - Static method in class jdistlib.math.MathFunctions: Batch call gamma function
GAUSSIAN - Enum constant in enum class jdistlib.CopulaFamily
GAUSSIAN - Enum constant in enum class jdistlib.math.density.Kernel
GaussianCopula - Class in jdistlib: Gaussian copula parameterized by a positive-definite correlation matrix.
GaussianCopula(double[][]) - Constructor for class jdistlib.GaussianCopula
GaussianReference - Interface in jdistlib.inference: Gaussian prior/reference measure used by elliptical slice and pCN updates.
GaussianRjBirthProposal - Class in jdistlib.inference: Candidate-specific or common Gaussian birth proposal.
GaussianRjBirthProposal(double[], double[]) - Constructor for class jdistlib.inference.GaussianRjBirthProposal
GaussianRjBirthProposal(double, double) - Constructor for class jdistlib.inference.GaussianRjBirthProposal
GaussianSparseCoefficientProposal - Class in jdistlib.inference: Independent Gaussian sparse-coefficient birth proposal.
GaussianSparseCoefficientProposal(double, double) - Constructor for class jdistlib.inference.GaussianSparseCoefficientProposal
gavrilovBenjaminiSarkar(double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Runs the Gavrilov-Benjamini-Sarkar adaptive step-down FDR procedure.
gavrilovBenjaminiSarkar(double[], double, int) - Static method in class jdistlib.disttest.MultipleTesting: Runs GBS for a declared total family size.
gcd(int, int) - Static method in class jdistlib.math.MathFunctions: Find greatest common divisor of m and n
GCV - Enum constant in enum class jdistlib.math.spline.SmoothSplineCriterion
GEMM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
GEMV - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
GeneralizedBetaSecondKind - Class in jdistlib: Four-parameter generalized beta distribution of the second kind (GB2).
GeneralizedBetaSecondKind(double, double, double, double) - Constructor for class jdistlib.GeneralizedBetaSecondKind
GeneralizedF - Class in jdistlib: Prentice generalized-F survival distribution used by flexsurv.
GeneralizedF(double, double, double, double) - Constructor for class jdistlib.GeneralizedF
GeneralizedGamma - Class in jdistlib: Stacy generalized gamma distribution as parameterized by VGAM.
GeneralizedGamma(double, double, double) - Constructor for class jdistlib.GeneralizedGamma
generalizedHyperbolic(double, double, double, double[], double[], double[][]) - Static method in class jdistlib.finance.MultivariateFinancialDistribution: Multivariate GH normal-variance mixture with W~GIG(lambda,chi,psi).
GeneralizedHyperbolicDistribution - Class in jdistlib.finance: Generalized-hyperbolic law in the canonical (lambda, alpha, beta, delta, mu) parameterization, with alpha > |beta| and delta > 0.
GeneralizedHyperbolicDistribution(double, double, double, double, double) - Constructor for class jdistlib.finance.GeneralizedHyperbolicDistribution
GeneralizedInverseGaussianDistribution - Class in jdistlib.finance: Generalized-inverse-Gaussian law in (lambda, chi, psi), chi/psi positive.
GeneralizedInverseGaussianDistribution(double, double, double) - Constructor for class jdistlib.finance.GeneralizedInverseGaussianDistribution
GeneralizedPareto - Class in jdistlib.evd: Generalized Pareto Distribution Taken from EVD package of R
GeneralizedPareto(double, double, double) - Constructor for class jdistlib.evd.GeneralizedPareto
generate(double[], RandomEngine) - Method in class jdistlib.inference.lang.CompiledModelScript
generate(String, String) - Static method in class jdistlib.inference.lang.ModelSourceGenerator
generate(RandomEngine) - Method in interface jdistlib.inference.SimulationBasedCalibration.Generator
GeneratedModelFactory - Interface in jdistlib.inference.lang: Contract implemented by ahead-of-time generated script wrappers.
GeneratedQuantity - Interface in jdistlib.inference: Named scalar generated from one retained unconstrained state.
GeneratedQuantitySink - Class in jdistlib.inference: Appends generated quantities to each state before forwarding it to another sink.
GeneratedQuantitySink(DrawSink, GeneratedQuantity...) - Constructor for class jdistlib.inference.GeneratedQuantitySink
GenericDistribution - Class in jdistlib.generic: An interface for a generic distribution.
GenericDistribution() - Constructor for class jdistlib.generic.GenericDistribution
geom_mean(double[]) - Static method in class jdistlib.math.VectorMath: Geometric mean
geom_sd(double[]) - Static method in class jdistlib.math.VectorMath: Geometric standard deviation (per Bug #34 request)
Geometric - Class in jdistlib
Geometric(double) - Constructor for class jdistlib.Geometric
geometricRatio(double) - Static method in class jdistlib.DiscreteTailBounds: Geometric/ratio-test bound.
GeometryAdvice - Class in jdistlib.inference: Coordinate associated with divergences and a scale/reparameterization suggestion.
GeometryAdvisor - Class in jdistlib.inference: Ranks coordinates whose divergent and non-divergent locations are most separated.
geometryFingerprint() - Method in class jdistlib.inference.WarmupBundle
GEQP3 - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
GER - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
GESVD - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
getAbsoluteError() - Method in class jdistlib.CopulaMeasureResult
getAbsoluteError() - Method in class jdistlib.finance.NumericalEstimate
getAbsoluteError() - Method in class jdistlib.math.ImmutableIntegrationResult
getAbsoluteMoment(double) - Method in class jdistlib.DistributionAnalysis: Returns the requested order's report, or null when it was not requested.
getAbsoluteMoments() - Method in class jdistlib.DistributionAnalysis
getAbsoluteTolerance() - Method in class jdistlib.math.IntegrationOptions
getAdaptiveProbeRounds() - Method in class jdistlib.FunctionAnalysisOptions: Number of rounds used to focus randomized probes around observed features.
getAdjustedPValues() - Method in class jdistlib.disttest.MultipleTesting.CensoredTestResult: Returns adjusted values for recorded tests.
getAllowedDiscrepancy() - Method in class jdistlib.math.IntegrationStabilityResult
getAlpha() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getAlpha() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getAlpha() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
getAlpha() - Method in class jdistlib.finance.StableDistribution
getAnalysis() - Method in class jdistlib.NumericalDistributionBuildResult
getAsk() - Method in class jdistlib.finance.OptionObservation
getAtomLocations() - Method in class jdistlib.finance.OptionImpliedDistribution
getAtomMasses() - Method in class jdistlib.finance.OptionImpliedDistribution
getAtoms() - Method in class jdistlib.NumericalSupport
getAttemptedEvaluations() - Method in class jdistlib.math.CallbackProfile
getAverageCallbackNanos() - Method in class jdistlib.math.CallbackProfile
getBandwidth() - Method in class jdistlib.finance.SmoothOptionDistributionResult
getBase() - Method in class jdistlib.RotatedCopula
getBaseDistribution() - Method in class jdistlib.CensoredDistribution
getBaseDistribution() - Method in class jdistlib.MonotoneTransformDistribution
getBaseDistribution() - Method in class jdistlib.TruncatedContinuousDistribution
getBaseline() - Method in class jdistlib.math.IntegrationStabilityResult
getBeta() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getBeta() - Method in class jdistlib.finance.StableDistribution
getBid() - Method in class jdistlib.finance.OptionObservation
getBoundaryDistances() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getBreakpoints() - Method in class jdistlib.math.IntegrationOptions
getC() - Method in class jdistlib.finance.CgmyDistribution
getCallbackExecution() - Method in class jdistlib.math.IntegrationOptions
getCallbackProfile() - Method in class jdistlib.math.ImmutableIntegrationResult
getCallbackProfile() - Method in class jdistlib.math.IntegrationResult: Returns immutable callback timing information.
getCancellation() - Method in class jdistlib.math.IntegrationOptions
getCandidateCount() - Method in class jdistlib.disttest.online.Saffron: Returns the number of candidate p-values seen so far.
getCandidateThreshold() - Method in class jdistlib.disttest.online.Saffron
getCauseMessage() - Method in class jdistlib.math.ImmutableIntegrationResult
getCauseType() - Method in class jdistlib.math.ImmutableIntegrationResult
getCdfEvaluations() - Method in class jdistlib.CopulaLogLikelihoodResult
getCdfEvaluations() - Method in class jdistlib.CopulaMeasureResult
getCdfTable() - Method in class jdistlib.NumericalContinuousDistribution: Returns the lazily built reusable monotone CDF table.
getChainProvenance() - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
getChi() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
getClassification() - Method in class jdistlib.CopulaDiagnostics
getCode() - Method in class jdistlib.DiagnosticFinding
getCode() - Method in enum class jdistlib.math.IntegrationStatus
getCoefficients() - Method in class jdistlib.math.Polynomial: Get the coefficients
getCompletedEvaluations() - Method in class jdistlib.math.CallbackProfile
getComponents() - Method in class jdistlib.MixtureDistribution
getConstructionPolicy() - Method in class jdistlib.FunctionAnalysisOptions
getContributions() - Method in class jdistlib.CopulaLogLikelihoodResult
getCopula() - Method in class jdistlib.CopulaDistribution
getCopula() - Method in class jdistlib.CopulaFitResult
getCopula() - Method in class jdistlib.MixedCopulaDistribution
getCopula() - Method in class jdistlib.PairCopula
getCopula() - Method in class jdistlib.VineFitResult
getCorrelation() - Method in class jdistlib.GaussianCopula
getCorrelation() - Method in class jdistlib.StudentTCopula
getCovariance() - Method in class jdistlib.finance.MultivariateFinancialDistribution
getCriterion() - Method in class jdistlib.CopulaSelectionResult
getCriticalValue() - Method in class jdistlib.disttest.MultipleTesting.StepDownFdrResult: Returns the rank-specific cutoff at the last rejection, or NaN.
getCriticalValues() - Method in class jdistlib.disttest.DiscreteFdr.Result: Returns tau_1 through tau_m.
getDegree() - Method in class jdistlib.math.Polynomial: Get the degree of the polynomial
getDegreesOfFreedom() - Method in class jdistlib.StudentTCopula
getDelta() - Method in class jdistlib.BB1Copula
getDelta() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getDerivativeStep() - Method in class jdistlib.CopulaMeasureOptions
getDerivativeStep() - Method in class jdistlib.PairCopula
getDetail() - Method in class jdistlib.math.ImmutableIntegrationResult
getDiagnostics() - Method in class jdistlib.CopulaFitResult
getDiagnostics() - Method in class jdistlib.finance.DistributionApproximation
getDiagnostics() - Method in class jdistlib.finance.OptionCurve
getDiagnostics() - Method in class jdistlib.VineFitResult
getDifferentiationUncertainty() - Method in class jdistlib.finance.SmoothOptionDistributionResult
getDiscontinuityRatio() - Method in class jdistlib.FunctionAnalysisOptions
getDiscount() - Method in class jdistlib.finance.OptionCurve
getDistribution() - Method in class jdistlib.CopulaMarginal
getDistribution() - Method in class jdistlib.finance.DistributionApproximation
getDistribution() - Method in class jdistlib.finance.DistributionFit.Result
getDistribution() - Method in class jdistlib.finance.DistributionTransforms.TiltResult
getDistribution() - Method in class jdistlib.finance.OptionCurve
getDistribution() - Method in class jdistlib.finance.SmoothOptionDistributionResult
getDynamicRangeOrders() - Method in class jdistlib.FunctionAnalysisOptions
getEstimatedTrueNulls() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns the first-stage estimate of the number of true nulls.
getEvaluationCount() - Method in class jdistlib.math.ImmutableIntegrationResult
getEvaluations() - Method in class jdistlib.finance.NumericalEstimate
getExceedances() - Method in class jdistlib.finance.ExtremeValueInference.ThresholdDiagnostics
getFactor() - Method in enum class jdistlib.math.density.Kernel
getFailure() - Method in class jdistlib.NumericalDistributionBuildResult
getFailureX() - Method in class jdistlib.math.ImmutableIntegrationResult
getFamily() - Method in class jdistlib.CopulaFitResult
getFinalLevel() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns the BH level used for the final stage.
getFindings() - Method in class jdistlib.DistributionAnalysis
getFindings() - Method in class jdistlib.FunctionAnalysis
getFiniteContributions() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getFirstAbsoluteMoment() - Method in class jdistlib.DistributionAnalysis: Returns the estimated first absolute moment, E[|X|].
getFirstProblemIndex() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getFirstProblemIndex() - Method in class jdistlib.CopulaLogLikelihoodResult
getFit() - Method in class jdistlib.finance.OptionCalibration.Result
getForward() - Method in class jdistlib.finance.OptionCurve
getG() - Method in class jdistlib.finance.CgmyDistribution
getGroupLabels() - Method in class jdistlib.disttest.MultipleTesting.GroupedFdrResult: Returns the sorted group labels corresponding to the group arrays.
getGroupPValues() - Method in class jdistlib.disttest.MultipleTesting.GroupedFdrResult: Returns one Simes p-value per group.
getImmutableNormalizationResult() - Method in class jdistlib.NumericalContinuousDistribution: Returns immutable normalization diagnostics without retaining the kernel.
getIncludedTerms() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getIndex() - Method in class jdistlib.disttest.online.OnlineFdrDecision: Returns the one-based arrival index.
getInitialFrequency() - Method in class jdistlib.finance.FourierInversionOptions
getInitialGuess() - Method in class jdistlib.math.opt.OptimizationConfig
getInitialIntervals() - Method in class jdistlib.CdfTableOptions
getInitialProbabilities() - Method in class jdistlib.PhaseType
getInitialTrustRegionRadius() - Method in class jdistlib.math.opt.BobyqaConfig
getIntegrationOptions() - Method in class jdistlib.FunctionAnalysisOptions
getIntegrationOptions() - Method in class jdistlib.NumericalContinuousDistribution: Returns the immutable integration settings used by this distribution.
getIntegrationWallNanos() - Method in class jdistlib.math.CallbackProfile
getIntensity() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getIntensity() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
getIntervals() - Method in class jdistlib.NumericalSupport
getInversionOptions() - Method in class jdistlib.finance.CgmyDistribution
getInversionOptions() - Method in class jdistlib.finance.LevyIncrementDistribution
getInversionOptions() - Method in class jdistlib.finance.MeixnerDistribution
getInversionOptions() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getInversionOptions() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
getIterations() - Method in class jdistlib.finance.DistributionFit.Result
getIterations() - Method in class jdistlib.finance.ImpliedVolatilityResult
getKernelValue() - Method in enum class jdistlib.math.density.Kernel
getKind() - Method in class jdistlib.Binomial.RandomState
getKind() - Method in class jdistlib.CopulaMarginal
getKind() - Method in class jdistlib.finance.DistributionFit.Observation
getKnotCount() - Method in class jdistlib.AdaptiveRejectionSampler
getLambda() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getLambda() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
getLeftStability() - Method in class jdistlib.AbsoluteMomentAnalysis: Null when the support has no interval on the left side.
getLeftValue() - Method in class jdistlib.AbsoluteMomentAnalysis
getLegacyStatusCode() - Method in class jdistlib.math.ImmutableIntegrationResult
getLocation() - Method in class jdistlib.finance.CgmyDistribution
getLocation() - Method in class jdistlib.finance.MeixnerDistribution
getLocation() - Method in class jdistlib.finance.MultivariateFinancialDistribution
getLocation() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getLocation() - Method in class jdistlib.finance.StableDistribution
getLogContributions() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getLogDensityUpperBound() - Method in class jdistlib.UniformRejectionEnvelope
getLogLikelihood() - Method in class jdistlib.CopulaFitResult
getLogLikelihood() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getLogLikelihood() - Method in class jdistlib.CopulaLogLikelihoodResult
getLogLikelihood() - Method in class jdistlib.VineFitResult
getLogMajorizationConstant() - Method in interface jdistlib.RejectionEnvelope: Returns log(M) in the majorization promise.
getLogMajorizationConstant() - Method in class jdistlib.UniformRejectionEnvelope
getLogNormalizationConstant() - Method in class jdistlib.NumericalContinuousDistribution: Returns the logarithm of the cached normalization constant.
getLogNormalizationConstant() - Method in class jdistlib.NumericalDiscreteDistribution: Returns the log normalization constant without overflow.
getLogNormalizationConstant() - Method in class jdistlib.NumericalPiecewiseDistribution
getLogNormalizer() - Method in class jdistlib.finance.DistributionTransforms.TiltResult
getLogScalingRegionCount() - Method in class jdistlib.NumericalContinuousDistribution: Number of independently scaled regions used for an automatic log-kernel.
getLogValue() - Method in class jdistlib.CopulaMeasureResult
getLower() - Method in class jdistlib.finance.DistributionFit.Observation
getLower() - Method in class jdistlib.finance.TransformDomain
getLower() - Method in class jdistlib.math.density.Bandwidth
getLower() - Method in class jdistlib.NumericalSupport.Interval
getLower() - Method in class jdistlib.ProbabilityInterval
getLowerAtomProbability() - Method in class jdistlib.CensoredDistribution
getLowerBound() - Method in class jdistlib.AsymmetricLaplace
getLowerBound() - Method in class jdistlib.BetaNegativeBinomial
getLowerBound() - Method in class jdistlib.BetaPrime
getLowerBound() - Method in class jdistlib.CensoredDistribution
getLowerBound() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getLowerBound() - Method in class jdistlib.DiscreteLaplace
getLowerBound() - Method in class jdistlib.DiscreteWeibull
getLowerBound() - Method in class jdistlib.ExponentiallyModifiedGaussian
getLowerBound() - Method in class jdistlib.FellerPareto
getLowerBound() - Method in class jdistlib.finance.ConditionalDistribution
getLowerBound() - Method in class jdistlib.finance.DelaporteDistribution
getLowerBound() - Method in class jdistlib.finance.EmpiricalDistribution
getLowerBound() - Method in class jdistlib.finance.FiniteGridDistribution
getLowerBound() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getLowerBound() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
getLowerBound() - Method in class jdistlib.finance.OptionImpliedDistribution
getLowerBound() - Method in class jdistlib.finance.OrderStatisticDistribution
getLowerBound() - Method in class jdistlib.finance.PolyaAeppliDistribution
getLowerBound() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
getLowerBound() - Method in class jdistlib.finance.StableDistribution
getLowerBound() - Method in class jdistlib.finance.CgmyDistribution
getLowerBound() - Method in class jdistlib.finance.LevyIncrementDistribution
getLowerBound() - Method in class jdistlib.finance.MeixnerDistribution
getLowerBound() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getLowerBound() - Method in class jdistlib.finance.VarianceGammaDistribution
getLowerBound() - Method in class jdistlib.Gamma
getLowerBound() - Method in class jdistlib.GeneralizedF
getLowerBound() - Method in class jdistlib.HalfCauchy
getLowerBound() - Method in class jdistlib.HalfT
getLowerBound() - Method in class jdistlib.Huber
getLowerBound() - Method in class jdistlib.LogitNormal
getLowerBound() - Method in class jdistlib.math.opt.OptimizationConfig
getLowerBound() - Method in class jdistlib.MixtureDistribution
getLowerBound() - Method in class jdistlib.MonotoneTransformDistribution
getLowerBound() - Method in class jdistlib.NegativeHypergeometric
getLowerBound() - Method in class jdistlib.Normal
getLowerBound() - Method in class jdistlib.NumericalContinuousDistribution: Returns the lower support bound.
getLowerBound() - Method in class jdistlib.NumericalDiscreteDistribution
getLowerBound() - Method in class jdistlib.NumericalPiecewiseDistribution
getLowerBound() - Method in class jdistlib.NumericalSupport
getLowerBound() - Method in class jdistlib.PhaseType
getLowerBound() - Method in class jdistlib.Poisson
getLowerBound() - Method in class jdistlib.Skellam
getLowerBound() - Method in class jdistlib.Slash
getLowerBound() - Method in interface jdistlib.SupportedDistribution
getLowerBound() - Method in class jdistlib.T
getLowerBound() - Method in class jdistlib.TruncatedContinuousDistribution
getLowerBound() - Method in class jdistlib.TukeyLambda
getLowerBound() - Method in class jdistlib.UniformRejectionEnvelope
getLowerBoundaryCoordinates() - Method in class jdistlib.CopulaDiagnostics
getLowerBracket() - Method in class jdistlib.finance.ImpliedVolatilityResult
getLowerPriceBound() - Method in class jdistlib.finance.ImpliedVolatilityResult
getM() - Method in class jdistlib.finance.CgmyDistribution
getM() - Method in class jdistlib.Wilcoxon
getMarginal(int) - Method in class jdistlib.CopulaDistribution
getMarginal(int) - Method in class jdistlib.MixedCopulaDistribution
getMarginals() - Method in class jdistlib.MixedCopulaDistribution
getMaturity() - Method in class jdistlib.finance.OptionCurve
getMaxCallbackNanos() - Method in class jdistlib.math.IntegrationOptions: Per-evaluation wall-clock limit, or Long.MAX_VALUE when disabled.
getMaxCdfEvaluations() - Method in class jdistlib.CopulaMeasureOptions
getMaxEvaluations() - Method in class jdistlib.math.IntegrationOptions
getMaximumAbsoluteError() - Method in class jdistlib.CopulaLogLikelihoodResult
getMaximumAttempts() - Method in class jdistlib.AdaptiveRejectionSampler
getMaximumCallbackNanos() - Method in class jdistlib.math.CallbackProfile
getMaximumDegreesOfFreedom() - Method in class jdistlib.CopulaFitOptions
getMaximumDiscrepancy() - Method in class jdistlib.math.IntegrationStabilityResult
getMaximumFrequency() - Method in class jdistlib.finance.FourierInversionOptions
getMaximumKnots() - Method in class jdistlib.AdaptiveRejectionSampler
getMaximumLogContribution() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getMaximumNodes() - Method in class jdistlib.CdfTableOptions
getMaximumPriceResidual() - Method in class jdistlib.finance.OptionCurve.Diagnostics
getMaximumPriceResidual() - Method in class jdistlib.finance.SmoothOptionDistributionResult
getMaximumQuantileRoundTripError() - Method in class jdistlib.DistributionAnalysis
getMaximumRefinements() - Method in class jdistlib.finance.FourierInversionOptions
getMaximumResidual() - Method in class jdistlib.finance.OptionCalibration.Result
getMaximumTailDisagreement() - Method in class jdistlib.DistributionAnalysis
getMaximumTerms() - Method in class jdistlib.CertifiedDiscreteOptions
getMaximumValidationError() - Method in class jdistlib.NumericalCdfTable
getMaximumValue() - Method in class jdistlib.FunctionAnalysis
getMaxNumFunctionCall() - Method in class jdistlib.math.opt.OptimizationConfig
getMaxTotalNanos() - Method in class jdistlib.math.IntegrationOptions: Total wall-clock limit, or Long.MAX_VALUE when disabled.
getMean() - Method in class jdistlib.DistributionAnalysis
getMeanExcess() - Method in class jdistlib.finance.ExtremeValueInference.ThresholdDiagnostics
getMeanLogContribution() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getMeasure() - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
getMessage() - Method in class jdistlib.CopulaDiagnostics
getMessage() - Method in class jdistlib.CopulaFitResult
getMessage() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getMessage() - Method in class jdistlib.CopulaLogLikelihoodResult
getMessage() - Method in class jdistlib.CopulaMeasureResult
getMessage() - Method in class jdistlib.DiagnosticFinding
getMessage() - Method in class jdistlib.finance.DistributionFit.Result
getMessage() - Method in enum class jdistlib.math.IntegrationStatus
getMessage() - Method in class jdistlib.VineFitResult
getMethod() - Method in class jdistlib.CopulaFitOptions
getMethod() - Method in class jdistlib.math.IntegrationOptions
getMethod() - Method in class jdistlib.ProbabilityInterval
getMid() - Method in class jdistlib.finance.OptionObservation
getMinimumBoundaryDistance() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getMinimumDegreesOfFreedom() - Method in class jdistlib.CopulaFitOptions
getMinimumLogContribution() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getMinimumPositiveValue() - Method in class jdistlib.FunctionAnalysis
getMinimumStep() - Method in class jdistlib.CopulaMeasureOptions
getMinimumTerms() - Method in class jdistlib.CertifiedDiscreteOptions
getMu() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getMu() - Method in class jdistlib.finance.VarianceGammaDistribution
getN() - Method in class jdistlib.Wilcoxon
getNegativeTolerance() - Method in class jdistlib.CopulaMeasureOptions
getNonFiniteContributions() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getNormalization() - Method in class jdistlib.finance.DistributionTransforms.TiltResult
getNormalizationConstant() - Method in class jdistlib.NumericalContinuousDistribution: Returns the cached normalization constant.
getNormalizationConstant() - Method in class jdistlib.NumericalDiscreteDistribution: Returns the normalization constant, or positive infinity if its magnitude exceeds the representable double range.
getNormalizationConstant() - Method in class jdistlib.NumericalPiecewiseDistribution
getNormalizationError() - Method in class jdistlib.finance.SmoothOptionDistributionResult
getNormalizationRelativeError() - Method in class jdistlib.DistributionAnalysis
getNormalizationResult() - Method in class jdistlib.NumericalContinuousDistribution: Returns a defensive copy of the normalization diagnostics.
getNormalizationStability() - Method in class jdistlib.FunctionAnalysis
getNumBins() - Method in class jdistlib.math.density.Bandwidth
getNumInterpolationPoints() - Method in class jdistlib.math.opt.BobyqaConfig
getObjective() - Method in class jdistlib.finance.DistributionFit.Result
getObjectiveFunction() - Method in class jdistlib.math.opt.OptimizationConfig
getObservations() - Method in class jdistlib.CopulaFitResult
getObservations() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getObservations() - Method in class jdistlib.CopulaLogLikelihoodResult
getObservations() - Method in class jdistlib.VineFitResult
getOmittedProbabilityTolerance() - Method in class jdistlib.CertifiedDiscreteOptions
getOmittedProbabilityUpperBound() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getOptimizationIterations() - Method in class jdistlib.CopulaFitOptions
getOptions() - Method in class jdistlib.MixedCopulaDistribution
getOrder() - Method in class jdistlib.AbsoluteMomentAnalysis
getOrders() - Method in class jdistlib.MomentAnalysisOptions
getOrigin() - Method in class jdistlib.finance.FiniteGridDistribution
getOriginalUndiscountedCalls() - Method in class jdistlib.finance.OptionCurve
getPairCopula(int, int) - Method in class jdistlib.CVineCopula
getPairCopula(int, int) - Method in class jdistlib.DVineCopula
getPairSelections() - Method in class jdistlib.VineFitResult
getPanels() - Method in class jdistlib.finance.FourierInversionOptions
getParameters() - Method in class jdistlib.CopulaFitResult
getParameters() - Method in class jdistlib.finance.DistributionFit.Result
getParameters() - Method in class jdistlib.VineFitResult
getProbabilities() - Method in class jdistlib.finance.FiniteGridDistribution
getProbabilities() - Method in class jdistlib.NumericalDiscreteDistribution: Returns probabilities corresponding to NumericalDiscreteDistribution.getSupport().
getProbability() - Method in class jdistlib.ProbabilityInterval
getProbability() - Method in class jdistlib.VineProbabilityResult
getPsi() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
getPValue() - Method in class jdistlib.disttest.online.OnlineFdrDecision: Returns the submitted p-value.
getRandomEngine() - Method in class jdistlib.generic.GenericDistribution
getRandomEngine() - Method in class jdistlib.SignRank
getRandomizedProbeBudget() - Method in class jdistlib.FunctionAnalysisOptions: Maximum number of seeded randomized probes performed after the grid.
getRandomizedSampledPoints() - Method in class jdistlib.FunctionAnalysis
getRandomSeed() - Method in class jdistlib.FunctionAnalysis
getRandomSeed() - Method in class jdistlib.FunctionAnalysisOptions: Seed that makes randomized probing reproducible.
getRankings() - Method in class jdistlib.CopulaSelectionResult
getRateMatrix() - Method in class jdistlib.PhaseType
getRefinementPasses() - Method in class jdistlib.CdfTableOptions
getRejected() - Method in class jdistlib.disttest.DiscreteFdr.Result
getRejected() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns rejection flags in input order; missing values are false.
getRejected() - Method in class jdistlib.disttest.MultipleTesting.CensoredTestResult: Returns rejection flags in input order; missing values are false.
getRejected() - Method in class jdistlib.disttest.MultipleTesting.GroupedFdrResult: Returns hypothesis-level rejection flags in input order.
getRejected() - Method in class jdistlib.disttest.MultipleTesting.StepDownFdrResult: Returns rejection flags in input order; missing values are false.
getRejectedCount() - Method in class jdistlib.disttest.DiscreteFdr.Result
getRejectedCount() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns the final number of rejected hypotheses.
getRejectedCount() - Method in class jdistlib.disttest.MultipleTesting.CensoredTestResult: Returns the number of recorded hypotheses rejected.
getRejectedCount() - Method in class jdistlib.disttest.MultipleTesting.StepDownFdrResult: Returns the number of rejected hypotheses.
getRejectionCount() - Method in class jdistlib.disttest.online.LordPlusPlus
getRejectionCount() - Method in interface jdistlib.disttest.online.OnlineFdrController: Returns the number of rejections so far.
getRejectionCount() - Method in class jdistlib.disttest.online.Saffron
getRelativeTolerance() - Method in class jdistlib.math.IntegrationOptions
getRepairedObservations() - Method in class jdistlib.finance.OptionCurve.Diagnostics
getRepeatabilityChecks() - Method in class jdistlib.FunctionAnalysisOptions
getResidual() - Method in class jdistlib.finance.ImpliedVolatilityResult
getResiduals() - Method in class jdistlib.finance.OptionCalibration.Result
getRetainedProbability() - Method in class jdistlib.TruncatedContinuousDistribution
GETRF - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
getRightStability() - Method in class jdistlib.AbsoluteMomentAnalysis: Null when the support has no interval on the right side.
getRightValue() - Method in class jdistlib.AbsoluteMomentAnalysis
getRotation() - Method in class jdistlib.RotatedCopula
getSampleCount() - Method in class jdistlib.FunctionAnalysisOptions
getSampledPoints() - Method in class jdistlib.FunctionAnalysis
getSamples() - Method in class jdistlib.VineProbabilityResult
getSamplingStrategy() - Method in class jdistlib.NumericalContinuousDistribution
getSamplingStrategy() - Method in class jdistlib.NumericalDiscreteDistribution
getSamplingStrategyExplanation() - Method in class jdistlib.NumericalContinuousDistribution
getSamplingStrategyExplanation() - Method in class jdistlib.NumericalDiscreteDistribution
getScale() - Method in class jdistlib.finance.MeixnerDistribution
getScale() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getScale() - Method in class jdistlib.finance.StableDistribution
getSecondAbsoluteMoment() - Method in class jdistlib.DistributionAnalysis: Returns the estimated second absolute moment, E[|X|^2].
getSeed() - Method in class jdistlib.finance.DistributionApproximation
getSeed() - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
getSeed() - Method in class jdistlib.rng.RandomEngine
getSelected() - Method in class jdistlib.CopulaSelectionResult
getSelectedGroupCount() - Method in class jdistlib.disttest.MultipleTesting.GroupedFdrResult: Returns the number of selected groups.
getSelectedGroups() - Method in class jdistlib.disttest.MultipleTesting.GroupedFdrResult: Returns group-selection flags in MultipleTesting.GroupedFdrResult.getGroupLabels() order.
getSeverity() - Method in class jdistlib.DiagnosticFinding
getShape() - Method in class jdistlib.finance.MeixnerDistribution
getShape() - Method in class jdistlib.finance.VarianceGammaDistribution
getSigma() - Method in class jdistlib.finance.VarianceGammaDistribution
getSingularities() - Method in class jdistlib.NumericalSupport
getSkew() - Method in class jdistlib.finance.MeixnerDistribution
getSkew() - Method in class jdistlib.finance.MultivariateFinancialDistribution
getSkew() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getSplit() - Method in class jdistlib.math.IntegrationStabilityResult
getSplitPoint() - Method in class jdistlib.AbsoluteMomentAnalysis
getSplitPoint() - Method in class jdistlib.MomentAnalysisOptions
getStageOneLevel() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns q/(1+q), the BH level used in stage one.
getStageOneRejections() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns the number rejected by the first-stage BH procedure.
getStandardError() - Method in class jdistlib.VineProbabilityResult
getStandardErrors() - Method in class jdistlib.finance.DistributionFit.Result
getStatus() - Method in class jdistlib.CopulaFitResult
getStatus() - Method in class jdistlib.CopulaLikelihoodDiagnostics
getStatus() - Method in class jdistlib.CopulaLogLikelihoodResult
getStatus() - Method in class jdistlib.CopulaMeasureResult
getStatus() - Method in class jdistlib.finance.ImpliedVolatilityResult
getStatus() - Method in class jdistlib.math.ImmutableIntegrationResult
getStatus() - Method in class jdistlib.math.IntegrationResult: Returns the typed interpretation of IntegrationResult.ier.
getStatus() - Method in class jdistlib.MultivariateProbabilityResult: Returns the typed terminal status.
getStatus() - Method in class jdistlib.VineFitResult
getStep() - Method in class jdistlib.finance.FiniteGridDistribution
getStoppingTrustRegionRadius() - Method in class jdistlib.math.opt.BobyqaConfig
getStrategy() - Method in class jdistlib.finance.NumericalEstimate
getStrike() - Method in class jdistlib.finance.OptionObservation
getStrikes() - Method in class jdistlib.finance.OptionCurve
getStructure() - Method in class jdistlib.VineFitResult
getSubdivisions() - Method in class jdistlib.math.ImmutableIntegrationResult
getSubdivisions() - Method in class jdistlib.math.IntegrationOptions
getSuccessfulContributions() - Method in class jdistlib.CopulaLogLikelihoodResult
getSuggestedBreakpoints() - Method in class jdistlib.FunctionAnalysis
getSupport() - Method in class jdistlib.disttest.DiscretePValueDistribution: Returns a defensive copy of the attainable p-values.
getSupport() - Method in class jdistlib.NumericalDiscreteDistribution: Returns the sorted declared support.
getSupport() - Method in class jdistlib.NumericalPiecewiseDistribution
getSupportDescription() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getTailIndex() - Method in class jdistlib.finance.ExtremeValueInference.ThresholdDiagnostics
getTailWeightUpperBound() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getTanhSinhMaxLevels() - Method in class jdistlib.math.IntegrationOptions
getTempering() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getTempering() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
getTestCount() - Method in class jdistlib.disttest.online.LordPlusPlus
getTestCount() - Method in interface jdistlib.disttest.online.OnlineFdrController: Returns the number of p-values processed.
getTestCount() - Method in class jdistlib.disttest.online.Saffron
getTestLevel() - Method in class jdistlib.disttest.online.OnlineFdrDecision: Returns the level chosen before this p-value was observed.
getTheta() - Method in class jdistlib.BB1Copula
getTheta() - Method in class jdistlib.ClaytonCopula
getTheta() - Method in class jdistlib.finance.DistributionTransforms.TiltResult
getTheta() - Method in class jdistlib.finance.VarianceGammaDistribution
getTheta() - Method in class jdistlib.FrankCopula
getTheta() - Method in class jdistlib.GumbelCopula
getTheta() - Method in class jdistlib.JoeCopula
getThreshold() - Method in class jdistlib.disttest.DiscreteFdr.Result: Returns the largest rejected observed p-value, or NaN.
getThreshold() - Method in class jdistlib.disttest.MultipleTesting.AdaptiveFdrResult: Returns the largest rejected raw p-value, or NaN.
getThreshold() - Method in class jdistlib.disttest.MultipleTesting.CensoredTestResult: Returns the largest rejected recorded raw p-value, or NaN.
getThreshold() - Method in class jdistlib.disttest.MultipleTesting.StepDownFdrResult: Returns the largest rejected raw p-value, or NaN.
getThresholds() - Method in class jdistlib.finance.ExtremeValueInference.ThresholdDiagnostics
getTightened() - Method in class jdistlib.math.IntegrationStabilityResult
getTime() - Method in class jdistlib.finance.LevyIncrementDistribution
getTolerance() - Method in class jdistlib.CdfTableOptions
getTolerance() - Method in class jdistlib.finance.FourierInversionOptions
getTolerance() - Method in class jdistlib.math.density.Bandwidth
getTotalCallbackNanos() - Method in class jdistlib.math.CallbackProfile
getTruncatedDistribution() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getUndiscountedCalls() - Method in class jdistlib.finance.OptionCurve
getUnitIncrement() - Method in class jdistlib.finance.LevyIncrementDistribution
getUnobservedCount() - Method in class jdistlib.disttest.MultipleTesting.CensoredTestResult: Returns the number of unrecorded hypotheses.
getUpper() - Method in class jdistlib.finance.DistributionFit.Observation
getUpper() - Method in class jdistlib.finance.TransformDomain
getUpper() - Method in class jdistlib.math.density.Bandwidth
getUpper() - Method in class jdistlib.NumericalSupport.Interval
getUpper() - Method in class jdistlib.ProbabilityInterval
getUpperAtomProbability() - Method in class jdistlib.CensoredDistribution
getUpperBound() - Method in class jdistlib.AsymmetricLaplace
getUpperBound() - Method in class jdistlib.BetaNegativeBinomial
getUpperBound() - Method in class jdistlib.BetaPrime
getUpperBound() - Method in class jdistlib.CensoredDistribution
getUpperBound() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
getUpperBound() - Method in class jdistlib.DiscreteLaplace
getUpperBound() - Method in class jdistlib.DiscreteWeibull
getUpperBound() - Method in class jdistlib.ExponentiallyModifiedGaussian
getUpperBound() - Method in class jdistlib.FellerPareto
getUpperBound() - Method in class jdistlib.finance.ConditionalDistribution
getUpperBound() - Method in class jdistlib.finance.DelaporteDistribution
getUpperBound() - Method in class jdistlib.finance.EmpiricalDistribution
getUpperBound() - Method in class jdistlib.finance.FiniteGridDistribution
getUpperBound() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
getUpperBound() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
getUpperBound() - Method in class jdistlib.finance.OptionImpliedDistribution
getUpperBound() - Method in class jdistlib.finance.OrderStatisticDistribution
getUpperBound() - Method in class jdistlib.finance.PolyaAeppliDistribution
getUpperBound() - Method in class jdistlib.finance.StableDistribution
getUpperBound() - Method in class jdistlib.finance.CgmyDistribution
getUpperBound() - Method in class jdistlib.finance.LevyIncrementDistribution
getUpperBound() - Method in class jdistlib.finance.MeixnerDistribution
getUpperBound() - Method in class jdistlib.finance.NormalTemperedStableDistribution
getUpperBound() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
getUpperBound() - Method in class jdistlib.finance.VarianceGammaDistribution
getUpperBound() - Method in class jdistlib.Gamma
getUpperBound() - Method in class jdistlib.GeneralizedF
getUpperBound() - Method in class jdistlib.HalfCauchy
getUpperBound() - Method in class jdistlib.HalfT
getUpperBound() - Method in class jdistlib.Huber
getUpperBound() - Method in class jdistlib.LogitNormal
getUpperBound() - Method in class jdistlib.math.opt.OptimizationConfig
getUpperBound() - Method in class jdistlib.MixtureDistribution
getUpperBound() - Method in class jdistlib.MonotoneTransformDistribution
getUpperBound() - Method in class jdistlib.NegativeHypergeometric
getUpperBound() - Method in class jdistlib.Normal
getUpperBound() - Method in class jdistlib.NumericalContinuousDistribution: Returns the upper support bound.
getUpperBound() - Method in class jdistlib.NumericalDiscreteDistribution
getUpperBound() - Method in class jdistlib.NumericalPiecewiseDistribution
getUpperBound() - Method in class jdistlib.NumericalSupport
getUpperBound() - Method in class jdistlib.PhaseType
getUpperBound() - Method in class jdistlib.Poisson
getUpperBound() - Method in class jdistlib.Skellam
getUpperBound() - Method in class jdistlib.Slash
getUpperBound() - Method in interface jdistlib.SupportedDistribution
getUpperBound() - Method in class jdistlib.T
getUpperBound() - Method in class jdistlib.TruncatedContinuousDistribution
getUpperBound() - Method in class jdistlib.TukeyLambda
getUpperBound() - Method in class jdistlib.UniformRejectionEnvelope
getUpperBoundaryCoordinates() - Method in class jdistlib.CopulaDiagnostics
getUpperBracket() - Method in class jdistlib.finance.ImpliedVolatilityResult
getUpperPriceBound() - Method in class jdistlib.finance.ImpliedVolatilityResult
getValue() - Method in class jdistlib.AbsoluteMomentAnalysis
getValue() - Method in class jdistlib.CopulaMeasureResult
getValue() - Method in exception class jdistlib.exception.PrecisionException
getValue() - Method in class jdistlib.finance.NumericalEstimate
getValue() - Method in class jdistlib.math.ImmutableIntegrationResult
getVariance() - Method in class jdistlib.DistributionAnalysis
getVolatility() - Method in class jdistlib.finance.ImpliedVolatilityResult
getWarning() - Method in class jdistlib.finance.NumericalEstimate
getWarning() - Method in class jdistlib.finance.OptionCalibration.Result
getWarningContributions() - Method in class jdistlib.CopulaLogLikelihoodResult
getWeight() - Method in class jdistlib.finance.DistributionFit.Observation
getWeight() - Method in class jdistlib.finance.OptionObservation
getWeightedRmse() - Method in class jdistlib.finance.OptionCurve.Diagnostics
getWeights() - Method in class jdistlib.MixtureDistribution
getWithinGroupLevel() - Method in class jdistlib.disttest.MultipleTesting.GroupedFdrResult: Returns the BH level used inside every selected group.
getX() - Method in class jdistlib.DiagnosticFinding
getY() - Method in class jdistlib.finance.CgmyDistribution
getZeroContributions() - Method in class jdistlib.CopulaLogLikelihoodResult
GEV - Class in jdistlib.evd: Generalized extreme value distribution.
GEV(double, double, double) - Constructor for class jdistlib.evd.GEV
gharmonic(int) - Static method in class jdistlib.math.MathFunctions: Calculate harmonic number
gharmonic(int, double) - Static method in class jdistlib.math.MathFunctions
gharmonic(int, double, double) - Static method in class jdistlib.math.MathFunctions: Calculate generalized harmonic number
GibbsKernel - Interface in jdistlib.inference: One exact or MCMC-within-Gibbs state update.
GibbsSampler - Class in jdistlib.inference: Composes exact, adaptive-rejection, Metropolis, or blocked Gibbs kernels.
GibbsSampler(GibbsKernel...) - Constructor for class jdistlib.inference.GibbsSampler
globalMemoryBytes() - Method in class jdistlib.accelerator.ComputeCapabilities
globalMemoryBytes() - Method in class jdistlib.accelerator.ComputeDeviceInfo
goalMet() - Method in class jdistlib.inference.PrecisionContinuationResult
Gompertz - Class in jdistlib: Gompertz distribution with shape and rate parameters.
Gompertz(double, double) - Constructor for class jdistlib.Gompertz
GPU - Enum constant in enum class jdistlib.accelerator.Compute: Require any available hardware accelerator.
GPU_PARALLEL - Enum constant in enum class jdistlib.accelerator.ExecutionKind
GPU_SERIAL - Enum constant in enum class jdistlib.accelerator.ExecutionKind
GradientCheckResult - Class in jdistlib.inference: Immutable comparison between supplied and finite-difference gradients.
gradientEvaluations() - Method in class jdistlib.inference.EvaluationCounter
GradientProvider - Interface in jdistlib.inference: Reports whether a differentiable target uses analytic rather than fallback gradients.
gradients() - Method in class jdistlib.accelerator.LogisticRegressionBatchResult
Gradients - Class in jdistlib.inference: Finite-difference adapters and gradient validation utilities.
graph() - Method in class jdistlib.inference.BayesianModel
grat_r(double, double, double, double) - Static method in class jdistlib.math.MathFunctions
GREATER - Enum constant in enum class jdistlib.disttest.TestKind
group(int) - Method in class jdistlib.inference.ObservationMetadata
groups() - Method in class jdistlib.inference.ObservationMetadata
gsumln(double, double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF THE FUNCTION LN(GAMMA(A + B)) FOR 1 <= A <= 2 AND 1 <= B <= 2 -----------------------------------------------------------------------
Gumbel - Class in jdistlib.evd: Gumbel distribution.
Gumbel(double, double) - Constructor for class jdistlib.evd.Gumbel
GUMBEL - Enum constant in enum class jdistlib.CopulaFamily
GumbelCopula - Class in jdistlib: Exchangeable Gumbel copula.
GumbelCopula(int, double) - Constructor for class jdistlib.GumbelCopula

H

HalfCauchy - Class in jdistlib: Half-Cauchy distribution with positive scale sigma.
HalfCauchy(double) - Constructor for class jdistlib.HalfCauchy
HalfNormal - Class in jdistlib: Half-normal distribution, the distribution of the absolute value of a zero-centered normal variate with scale sigma.
HalfNormal(double) - Constructor for class jdistlib.HalfNormal
HalfT - Class in jdistlib: Half-Student-t distribution with degrees of freedom and scale.
HalfT(double, double) - Constructor for class jdistlib.HalfT
HamiltonianMonteCarlo - Class in jdistlib.inference: Fixed-trajectory HMC with dual-averaged step size and covariance adaptation.
HamiltonianMonteCarlo() - Constructor for class jdistlib.inference.HamiltonianMonteCarlo
harm_mean(double[]) - Static method in class jdistlib.math.VectorMath: Harmonic mean
hasAnalyticGradient() - Method in class jdistlib.inference.autodiff.ReverseModeLogDensity
hasAnalyticGradient() - Method in class jdistlib.inference.BayesianModel
hasAnalyticGradient() - Method in interface jdistlib.inference.GradientProvider
hasAnalyticGradient() - Method in class jdistlib.inference.ModelEvaluator
hasAtoms() - Method in class jdistlib.NumericalSupport
hasErrors() - Method in class jdistlib.DistributionAnalysis
hasErrors() - Method in class jdistlib.FunctionAnalysis
hasEstimate() - Method in class jdistlib.CopulaLogLikelihoodResult
hasEstimate() - Method in class jdistlib.CopulaMeasureResult
hasEstimate() - Method in class jdistlib.MultivariateProbabilityResult: Returns whether this object contains a usable numerical estimate.
hash(String) - Static method in class jdistlib.inference.lang.ModelSourceGenerator
hashCode() - Method in class jdistlib.inference.lang.TupleValue
hashCode() - Method in class jdistlib.inference.ObservationMetadata
hashCode() - Method in class jdistlib.inference.ReversibleJumpState
hashCode() - Method in class jdistlib.inference.SparseSubsetState
hashCode() - Method in class jdistlib.math.Complex
hasParameter(String) - Method in class jdistlib.inference.ModelState
hasWarning() - Method in class jdistlib.finance.NumericalEstimate
hasWarnings() - Method in class jdistlib.DistributionAnalysis
hasWarnings() - Method in class jdistlib.FunctionAnalysis
hazard(double[], boolean) - Method in class jdistlib.generic.GenericDistribution
hazard(double, boolean) - Method in class jdistlib.generic.GenericDistribution: Hazard function of a distribution.
hazard(double, double, double, boolean) - Static method in class jdistlib.Gompertz: Returns the hazard rate * exp(shape * x).
HealthIssue - Class in jdistlib.inference: Diagnostic code, quantitative evidence, and an actionable remediation.
HealthSeverity - Enum Class in jdistlib.inference: Machine-readable inference health severity.
healthy() - Method in class jdistlib.inference.Fit
healthy() - Method in class jdistlib.inference.InferenceHealth
healthy() - Method in class jdistlib.inference.SamplerDiagnostics
HigherIndexDaeSolver - Class in jdistlib.inference.solver: Projected velocity-Verlet solver for holonomic index-3 mechanical DAEs.
HigherIndexDaeSolver.Result - Class in jdistlib.inference.solver: Position/velocity trajectory and maximum observed constraint residual.
highVarianceObservations() - Method in class jdistlib.inference.Waic.Result
hill(double[], int) - Static method in class jdistlib.finance.ExtremeValueInference
historySize() - Method in class jdistlib.inference.PathfinderOptions
historySize(int) - Method in class jdistlib.inference.PathfinderOptions.Builder
HOCHBERG - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Hochberg step-up control under independence or positive dependence.
hole(double, double) - Method in class jdistlib.NumericalSupport.Builder: Removes an open interval from every declared continuous interval.
HOLM - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Holm step-down family-wise error-rate control.
HOLM_SIDAK - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Holm-Sidak step-down control for independent tests.
HolonomicDaeSystem - Interface in jdistlib.inference.solver: Mechanical index-3 DAE described by acceleration and holonomic constraints.
HOMMEL - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Hommel control under independence or positive dependence.
Huber - Class in jdistlib: Huber least-favourable distribution with Gaussian center and exponential tails.
Huber(double, double, double) - Constructor for class jdistlib.Huber
HurdleNegativeBinomial - Class in jdistlib: Hurdle negative binomial with pi denoting positive-count mass.
HurdleNegativeBinomial(double, double, double) - Constructor for class jdistlib.HurdleNegativeBinomial
HurdlePoisson - Class in jdistlib: Hurdle Poisson with pi denoting the probability of being positive.
HurdlePoisson(double, double) - Constructor for class jdistlib.HurdlePoisson
HybridKernel - Interface in jdistlib.inference: One support-aware transition in a scheduled hybrid sampler.
HybridKernelTransition - Class in jdistlib.inference: Outcome of one hybrid-kernel update.
HybridKernelTransition(double, boolean, double, boolean) - Constructor for class jdistlib.inference.HybridKernelTransition
HybridSampler - Class in jdistlib.inference: Scheduled support-aware sampler for fixed-dimensional mixed continuous/discrete targets.
HybridSampler(MixedStateSpace, HybridKernel...) - Constructor for class jdistlib.inference.HybridSampler
HybridSamplerDiagnostics - Class in jdistlib.inference: Per-kernel acceptance and support diagnostics for a hybrid schedule.
HybridSamplingResult - Class in jdistlib.inference: Retained mixed-state chain and diagnostics from its scheduled kernels.
HyperGeometric - Class in jdistlib
HyperGeometric(double, double, double) - Constructor for class jdistlib.HyperGeometric
HyperGeometric.RandomState - Class in jdistlib

I

i(double, double, boolean) - Static method in class jdistlib.math.Bessel: This routine calculates Bessel functions I_{alpha} (x) for non-negative argument x, and order alpha, with or without exponential scaling.
I - Static variable in class jdistlib.math.Complex
IAMAX - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
id() - Method in interface jdistlib.accelerator.ComputeBackend
id() - Method in class jdistlib.accelerator.CpuComputeBackend
id() - Method in class jdistlib.inference.ModelGraph.Node
idamax(int, double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend: Returns the zero-based logical index of the first absolute maximum, or -1 when empty.
ier - Variable in class jdistlib.math.IntegrationResult
imaginary() - Method in class jdistlib.math.Complex
ImmutableIntegrationResult - Class in jdistlib.math: Immutable modern integration result.
impliedBachelier(double, double, double, double, double, boolean) - Static method in class jdistlib.finance.ReferenceOptions
impliedBlackScholes(double, double, double, double, double, boolean) - Static method in class jdistlib.finance.ReferenceOptions
ImpliedVolatilityResult - Class in jdistlib.finance: Checked implied-volatility inversion result.
ImpliedVolatilityResult.Status - Enum Class in jdistlib.finance
inclusionCounts() - Method in class jdistlib.inference.SparseSubsetCheckpoint
inclusionEffectiveSampleSizes() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
inclusionMcses() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
inclusionProbabilities() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
inclusionProbability(int) - Method in class jdistlib.inference.SparseSubsetSummary
inclusionRHats() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
INCOMPATIBLE_DEPENDENCE - Enum constant in enum class jdistlib.CopulaFitResult.Status
INDEPENDENCE - Enum constant in enum class jdistlib.CopulaFamily
IndependenceCopula - Class in jdistlib: Product copula representing mutual independence.
IndependenceCopula(int) - Constructor for class jdistlib.IndependenceCopula
index() - Method in class jdistlib.inference.ShrinkageSelection.Variable
index(double[], int[]) - Static method in class jdistlib.util.Utilities: Mimic x[idx] behavior of R
index_min1(double[], int[]) - Static method in class jdistlib.util.Utilities: Mimic x[idx] behavior of R
indicatorEss(double[][], Predicate<double[]>) - Static method in class jdistlib.inference.MonteCarloError
Inference - Class in jdistlib.inference: Concise facade for reproducible multi-chain fitting.
InferenceCliOptions - Class in jdistlib.inference: Parses reusable compute switches for command-line applications embedding JDistlib.
InferenceGraphExport - Class in jdistlib.inference: Dependency-free JSON, tidy CSV, and SVG adapters for chart-neutral data.
InferenceHealth - Class in jdistlib.inference: Actionable policy over sampler and posterior diagnostics.
InferenceHtmlReport - Class in jdistlib.inference: Self-contained headless HTML report composed from diagnostic data and SVGs.
infinityNorm(double[]) - Static method in class jdistlib.inference.solver.AlgebraicSolver
INFO - Enum constant in enum class jdistlib.DiagnosticFinding.Severity
INFO - Enum constant in enum class jdistlib.inference.HealthSeverity
INITIAL_FAST - Enum constant in enum class jdistlib.inference.WarmupSchedule.Phase
initialBuffer() - Method in class jdistlib.inference.WarmupSchedule
initialBuffer() - Method in class jdistlib.inference.WarmupSchedule.Resolved
initialGuess - Variable in class jdistlib.math.opt.OptimizationConfig
initialIntervals(int) - Method in class jdistlib.CdfTableOptions.Builder
initialInverseMassMatrix() - Method in class jdistlib.inference.MetricConfiguration
initialize(DifferentiableLogDensity, double[], RandomEngine) - Static method in class jdistlib.inference.PathfinderInitializer
initialize(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.RandomWalkKernel
initialize(LogDensity, double[], SamplingOptions, RandomEngine) - Method in interface jdistlib.inference.TransitionKernel
initialState() - Method in class jdistlib.inference.BayesianModel
initialState() - Method in class jdistlib.inference.PathfinderFit
initialState() - Method in class jdistlib.inference.PathfinderResult
initialState() - Method in interface jdistlib.inference.SimulationBasedCalibration.Simulation
initialStates() - Method in class jdistlib.inference.SuperchainPlan
InitialStates - Class in jdistlib.inference: Deterministic validation, constrained initialization, and bounded retry helpers.
initialStep - Variable in class jdistlib.inference.solver.OdeSolver.Options
initialStep - Variable in class jdistlib.inference.solver.StiffOdeSolver.Options
initialStepSize() - Method in class jdistlib.inference.SamplerCheckpoint
initialStepSize() - Method in class jdistlib.inference.WarmupResult
initialTrustRegionRadius - Variable in class jdistlib.math.opt.BobyqaConfig
initialWindow() - Method in class jdistlib.inference.WarmupSchedule
integer() - Static method in class jdistlib.inference.CoordinateSupport
integer(int, int) - Static method in class jdistlib.inference.CoordinateSupport
INTEGER - Enum constant in enum class jdistlib.inference.CoordinateSupport.Kind
integerSupport(int, int) - Method in class jdistlib.NumericalDiscreteDistribution.Builder
integrate() - Method in class jdistlib.math.Polynomial: Compute the integral of this polynomial.
integrate(double) - Method in class jdistlib.math.Polynomial: Compute the integral of this polynomial.
integrate(double, double) - Method in class jdistlib.math.Polynomial: Compute a definite integral bounded by (a, b)
integrate(DaeSystem, double[], double, double[], double[], double[], AlgebraicSolver.Options) - Static method in class jdistlib.inference.solver.DaeSolver: Integrates at requested increasing times using implicit Euler and Newton iterations.
integrate(HolonomicDaeSystem, double[], double[], double, double[], double, double, int, double[], double[]) - Static method in class jdistlib.inference.solver.HigherIndexDaeSolver: Integrates with fixed maximum step and Newton position/velocity projection.
integrate(OdeSystem, double[], double, double[], double[], double[], OdeSolver.Options) - Static method in class jdistlib.inference.solver.OdeSolver: Integrates from initialTime; output row i corresponds to times[i].
integrate(OdeSystem, double[], double, double[], double[], double[], StiffOdeSolver.Options) - Static method in class jdistlib.inference.solver.StiffOdeSolver: Integrates to each strictly increasing output time with step-doubling error control.
integrate(UnivariateFunction, double, double) - Static method in class jdistlib.math.Integrate: Integrates f over a finite, semi-infinite, or infinite interval.
integrate(UnivariateFunction, double, double, double, double, int) - Static method in class jdistlib.math.Integrate: Integrates f with QUADPACK-compatible status codes.
integrate(UnivariateFunction, double, double, IntegrationOptions) - Static method in class jdistlib.math.Integrate: Integrates with hardened callback handling, evaluation budgets, optional breakpoints, cancellation, and selectable quadrature methods.
Integrate - Class in jdistlib.math: Adaptive numerical integration corresponding to R 4.6.1 stats::integrate.
integrateImmutable(UnivariateFunction, double, double) - Static method in class jdistlib.math.Integrate: Integrates with hardened defaults and returns an immutable modern result.
integrateImmutable(UnivariateFunction, double, double, IntegrationOptions) - Static method in class jdistlib.math.Integrate: Integrates with hardened options and returns an immutable modern result.
integrateWithSensitivities(DaeSystem, double[], double, double[], double[], double[], AlgebraicSolver.Options) - Static method in class jdistlib.inference.solver.DaeSolver: Differentiates a DAE trajectory by consistently perturbing each parameter.
integrateWithSensitivities(OdeSystem, double[], double, double[], double[], double[], OdeSolver.Options) - Static method in class jdistlib.inference.solver.OdeSolver: Integrates the state and forward parameter-sensitivity equations.
IntegrationJson - Class in jdistlib.math: Dependency-free JSON serialization for integration diagnostics.
integrationOptions(IntegrationOptions) - Method in class jdistlib.FunctionAnalysisOptions.Builder
integrationOptions(IntegrationOptions) - Method in class jdistlib.NumericalContinuousDistribution.Builder
integrationOptions(IntegrationOptions) - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
IntegrationOptions - Class in jdistlib.math: Immutable options for hardened numerical integration.
IntegrationOptions.Builder - Class in jdistlib.math: Builder for IntegrationOptions.
IntegrationOptions.CallbackExecution - Enum Class in jdistlib.math: Where opt-in hardened callback evaluations execute.
IntegrationOptions.Method - Enum Class in jdistlib.math: Available integration strategies.
IntegrationResult - Class in jdistlib.math
IntegrationResult() - Constructor for class jdistlib.math.IntegrationResult
IntegrationStabilityResult - Class in jdistlib.math: Results from repeating an integral under stricter and differently split settings.
IntegrationStatus - Enum Class in jdistlib.math: Stable, typed interpretation of legacy QUADPACK-compatible status codes.
integrationTime() - Method in class jdistlib.inference.AdaptiveStaticHmcResult
integrationTime() - Method in class jdistlib.inference.SamplingOptions: Static-HMC integration time; NaN retains the legacy fixed leapfrog count.
integrationTime(double) - Method in class jdistlib.inference.SamplingOptions.Builder
INTERIOR - Enum constant in enum class jdistlib.CopulaDiagnostics.Classification
interval(double, double) - Static method in class jdistlib.finance.DistributionFit.Observation
interval(double, double) - Method in class jdistlib.NumericalSupport.Builder
interval(double, double) - Static method in class jdistlib.NumericalSupport
INTERVAL - Enum constant in enum class jdistlib.finance.DistributionFit.Observation.Kind
invalid(String) - Static method in class jdistlib.inference.ReversibleJumpProposal
INVALID - Enum constant in enum class jdistlib.CopulaDiagnostics.Classification
INVALID_DATA - Enum constant in enum class jdistlib.CopulaFitResult.Status
INVALID_DATA - Enum constant in enum class jdistlib.CopulaLikelihoodDiagnostics.Status
INVALID_DATA - Enum constant in enum class jdistlib.VineFitResult.Status
INVALID_INITIAL_STATE - Enum constant in enum class jdistlib.inference.ChainResult.Status
INVALID_INITIAL_STATE - Enum constant in enum class jdistlib.inference.ReversibleJumpResult.Status
INVALID_INITIAL_STATE - Enum constant in enum class jdistlib.inference.SparseSubsetResult.Status
INVALID_INPUT - Enum constant in enum class jdistlib.CopulaLogLikelihoodResult.Status
INVALID_INPUT - Enum constant in enum class jdistlib.CopulaMeasureResult.Status
INVALID_INPUT - Enum constant in enum class jdistlib.finance.ImpliedVolatilityResult.Status
INVALID_INPUT - Enum constant in enum class jdistlib.math.IntegrationStatus
INVALID_INPUT - Enum constant in enum class jdistlib.MultivariateProbabilityStatus: Parameters, bounds, options, or the random stream were invalid.
INVALID_INPUT - Static variable in class jdistlib.MultivariateProbabilityResult: Legacy integer code corresponding to MultivariateProbabilityStatus.INVALID_INPUT.
invalidProposal() - Method in class jdistlib.inference.ReversibleJumpIterationStats
invalidProposal() - Method in class jdistlib.inference.SparseSubsetIterationStats
invalidProposals() - Method in class jdistlib.inference.SparseSubsetCheckpoint
invalidProposals(int) - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
invalidProposals(int) - Method in class jdistlib.inference.ReversibleJumpResult
inverse(ReversibleJumpState, double[]) - Method in class jdistlib.inference.CoordinateInsertionTransformation
inverse(ReversibleJumpState, double[]) - Method in class jdistlib.inference.CoordinateSplitTransformation
inverse(ReversibleJumpState, double[]) - Method in interface jdistlib.inference.DimensionMatchingTransformation
INVERSE_CDF - Enum constant in enum class jdistlib.SamplingStrategy
inverse_survival(double[], boolean) - Method in class jdistlib.generic.GenericDistribution
inverse_survival(double, boolean) - Method in class jdistlib.generic.GenericDistribution: Inverse survival function, which is basically quantile(1-p).
inverseFirstGivenSecond(double, double) - Method in class jdistlib.PairCopula: Inverts PairCopula.conditionalFirstGivenSecond(double, double) in its first argument.
inverseHessians() - Method in class jdistlib.inference.OptimizationTrace
inverseMassDiagonal() - Method in class jdistlib.inference.WarmupResult
inverseMassMatrix() - Method in class jdistlib.inference.SamplerCheckpoint
inverseMassMatrix() - Method in class jdistlib.inference.WarmupBundle
inverseMassMatrix() - Method in class jdistlib.inference.WarmupResult
inverseSecondGivenFirst(double, double) - Method in class jdistlib.PairCopula: Inverts PairCopula.conditionalSecondGivenFirst(double, double) in its second argument.
InvGamma - Class in jdistlib
InvGamma(double, double) - Constructor for class jdistlib.InvGamma
InvNormal - Class in jdistlib: Inverse normal (or Wald) distribution.
InvNormal(double, double) - Constructor for class jdistlib.InvNormal
iqr(double[]) - Static method in class jdistlib.math.VectorMath: Inter-quartile range (i.e., Q3 - Q1)
is_duplicated(double[]) - Static method in class jdistlib.util.Utilities
is_duplicated(S[]) - Static method in class jdistlib.util.Utilities
isAdaptiveRejectionSamplingConfigured() - Method in class jdistlib.NumericalContinuousDistribution
isamax(int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend: Returns the zero-based logical index of the first absolute maximum, or -1 when empty.
isBoundary() - Method in class jdistlib.CopulaDiagnostics
isCall() - Method in class jdistlib.finance.OptionObservation
isContinuous() - Method in class jdistlib.CopulaMarginal
isConverged() - Method in class jdistlib.finance.DistributionFit.Result
isConverged() - Method in class jdistlib.finance.ImpliedVolatilityResult
isConverged() - Method in class jdistlib.finance.NumericalEstimate
isConverged() - Method in class jdistlib.MultivariateProbabilityResult: Alias emphasizing convergence rather than validity.
isConvex() - Method in class jdistlib.finance.OptionCurve.Diagnostics
isDensityDefined() - Method in class jdistlib.CopulaDiagnostics
isDifferentiable() - Method in class jdistlib.inference.FactorSpec
isDiscrete() - Method in class jdistlib.CopulaMarginal
isEqual(double, double, double) - Static method in class jdistlib.math.VectorMath
isEqualScaled(double, double, double) - Static method in class jdistlib.math.VectorMath
isFinite(double) - Static method in class jdistlib.math.MathFunctions
isIdentifiable() - Method in class jdistlib.finance.OptionCalibration.Result
isInfinite(double) - Static method in class jdistlib.math.MathFunctions
isInterior() - Method in class jdistlib.CopulaDiagnostics
isLeftStable() - Method in class jdistlib.AbsoluteMomentAnalysis
isLowerIncluded() - Method in class jdistlib.finance.TransformDomain
isMinimize - Variable in class jdistlib.math.opt.OptimizationConfig
isMinimize() - Method in class jdistlib.math.opt.OptimizationConfig
isMinimum - Variable in class jdistlib.math.opt.OptimizationResult
isMonotone() - Method in class jdistlib.finance.OptionCurve.Diagnostics
isNonInt(double) - Static method in class jdistlib.math.MathFunctions
isNormalized() - Method in class jdistlib.finance.OptionCurve.Diagnostics
ISOLATED_DAEMON - Enum constant in enum class jdistlib.math.IntegrationOptions.CallbackExecution: Evaluate on a private daemon worker so a time limit can release the caller.
isRejected() - Method in class jdistlib.disttest.online.OnlineFdrDecision: Returns whether the hypothesis was rejected.
isRejectionSamplingConfigured() - Method in class jdistlib.NumericalContinuousDistribution
isReliable(double) - Method in class jdistlib.finance.SmoothOptionDistributionResult
isRightStable() - Method in class jdistlib.AbsoluteMomentAnalysis
isSaturated() - Method in class jdistlib.NumericalCdfTable
isSorted(double[], boolean) - Static method in class jdistlib.math.VectorMath
isStable() - Method in class jdistlib.AbsoluteMomentAnalysis
isStable() - Method in class jdistlib.math.IntegrationStabilityResult
isSuccess() - Method in class jdistlib.CopulaFitResult
isSuccess() - Method in class jdistlib.CopulaLikelihoodDiagnostics
isSuccess() - Method in class jdistlib.CopulaLogLikelihoodResult
isSuccess() - Method in class jdistlib.CopulaMeasureResult
isSuccess() - Method in class jdistlib.CopulaSelectionResult
isSuccess() - Method in class jdistlib.math.ImmutableIntegrationResult
isSuccess() - Method in class jdistlib.math.IntegrationResult
isSuccess() - Method in class jdistlib.MultivariateProbabilityResult: Returns whether the requested numerical tolerance was met.
isSuccess() - Method in class jdistlib.VineFitResult
issues() - Method in class jdistlib.inference.InferenceHealth
isSuitableForConstruction() - Method in class jdistlib.FunctionAnalysis: True means no error was observed; it is not a mathematical proof.
isSuitableForConstruction(ConstructionPolicy) - Method in class jdistlib.FunctionAnalysis: Applies an explicit policy to the retained findings.
isUpperIncluded() - Method in class jdistlib.finance.TransformDomain
isValid() - Method in class jdistlib.CopulaDiagnostics
isValid() - Method in class jdistlib.MultivariateProbabilityOptions: Returns whether all tolerances and work limits are usable.
iteration() - Method in class jdistlib.inference.WarmupTrace.Entry
iterations() - Method in class jdistlib.inference.OptimizationResult
iterations() - Method in class jdistlib.inference.PredictiveStacking.Result
iterations() - Method in class jdistlib.inference.solver.AlgebraicSolver.Result
iterations() - Method in class jdistlib.inference.WarmupResult
IterationStats - Class in jdistlib.inference: Per-iteration sampler statistics used by convergence diagnostics.
IterationStats(boolean, double, double, double, double, boolean, int, boolean, int) - Constructor for class jdistlib.inference.IterationStats
IterationStats(boolean, double, double, double, double, boolean, int, boolean, int, double) - Constructor for class jdistlib.inference.IterationStats
IterationStats(boolean, double, double, double, double, boolean, int, int) - Constructor for class jdistlib.inference.IterationStats
iterator() - Method in class jdistlib.inference.lang.TupleValue

J

j - Variable in class jdistlib.evd.Order
j(double, double) - Static method in class jdistlib.math.Bessel: Calculates Bessel functions J_{alpha} (x) for non-negative argument x, and order alpha.
jacobian() - Method in class jdistlib.inference.lang.ExternalFunctionResult
jarque_bera_pvalue(double) - Static method in class jdistlib.disttest.NormalityTest
jarque_bera_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest: Calculate Jarque-Bera Normality Test.
JAVA_CPU - Enum constant in enum class jdistlib.accelerator.ComputeApi
JAVA_REFERENCE - Enum constant in enum class jdistlib.accelerator.ExecutionKind
Java notes - Search tag in class jdistlib.rng.MersenneTwister: Section
Java notes - Search tag in class jdistlib.rng.MersenneTwisterSafe: Section
jdistlib - package jdistlib
jdistlib.accelerator - package jdistlib.accelerator
jdistlib.disttest - package jdistlib.disttest
jdistlib.disttest.online - package jdistlib.disttest.online
jdistlib.evd - package jdistlib.evd
jdistlib.exception - package jdistlib.exception
jdistlib.finance - package jdistlib.finance
jdistlib.generic - package jdistlib.generic
jdistlib.inference - package jdistlib.inference
jdistlib.inference.autodiff - package jdistlib.inference.autodiff
jdistlib.inference.lang - package jdistlib.inference.lang
jdistlib.inference.solver - package jdistlib.inference.solver
jdistlib.math - package jdistlib.math
jdistlib.math.approx - package jdistlib.math.approx
jdistlib.math.density - package jdistlib.math.density
jdistlib.math.opt - package jdistlib.math.opt
jdistlib.math.spline - package jdistlib.math.spline
jdistlib.matrix - package jdistlib.matrix
jdistlib.rng - package jdistlib.rng
jdistlib.util - package jdistlib.util
jitter() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
jitter(double) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
JOE - Enum constant in enum class jdistlib.CopulaFamily
JoeCopula - Class in jdistlib: Bivariate Joe copula with upper-tail dependence and theta >= 1.
JoeCopula(double) - Constructor for class jdistlib.JoeCopula
jumpAcceptanceProbability() - Method in class jdistlib.inference.ReversibleJumpIterationStats
jumpAcceptanceProbability() - Method in class jdistlib.inference.SparseSubsetIterationStats
jumpAccepted() - Method in class jdistlib.inference.ReversibleJumpIterationStats
jumpAccepted() - Method in class jdistlib.inference.SparseSubsetIterationStats
jumpAttempted() - Method in class jdistlib.inference.ReversibleJumpIterationStats

K

k - Variable in class jdistlib.HyperGeometric.RandomState
k(double, double, boolean) - Static method in class jdistlib.math.Bessel: This routine calculates modified Bessel functions of the third kind, K_{alpha} (x), for non-negative argument x, and order alpha, with or without exponential scaling.
kDefaultEpsilon - Static variable in class jdistlib.math.spline.SmoothSpline
kDefaultMaxNumIterations - Static variable in class jdistlib.math.spline.SmoothSpline
kDefaultSmoothingParamLowerBound - Static variable in class jdistlib.math.spline.SmoothSpline
kDefaultSmoothingParamUpperBound - Static variable in class jdistlib.math.spline.SmoothSpline
kDefaultTolerance - Static variable in class jdistlib.math.spline.SmoothSpline
Kendall - Class in jdistlib: Kendall tau distribution
Kendall(int) - Constructor for class jdistlib.Kendall
KENDALL_TAU - Enum constant in enum class jdistlib.CopulaFitOptions.Method
kendallsTau() - Method in interface jdistlib.Copula: Matrix of all pairwise Kendall's tau values.
kendallsTau(double[][]) - Static method in class jdistlib.CopulaFitter: Pairwise empirical Kendall tau computed over untied pairs.
kendallsTau(int, int) - Method in class jdistlib.BB1Copula
kendallsTau(int, int) - Method in class jdistlib.ClaytonCopula
kendallsTau(int, int) - Method in interface jdistlib.Copula: Kendall's tau for a coordinate pair.
kendallsTau(int, int) - Method in class jdistlib.CVineCopula
kendallsTau(int, int) - Method in class jdistlib.DVineCopula
kendallsTau(int, int) - Method in class jdistlib.FrankCopula
kendallsTau(int, int) - Method in class jdistlib.GaussianCopula
kendallsTau(int, int) - Method in class jdistlib.GumbelCopula
kendallsTau(int, int) - Method in class jdistlib.IndependenceCopula
kendallsTau(int, int) - Method in class jdistlib.JoeCopula
kendallsTau(int, int) - Method in class jdistlib.RotatedCopula
kendallsTau(int, int) - Method in class jdistlib.StudentTCopula
kernel(UnivariateFunction) - Method in class jdistlib.NumericalContinuousDistribution.Builder
kernel(UnivariateFunction) - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
Kernel - Enum Class in jdistlib.math.density
kernelCount() - Method in class jdistlib.inference.HybridSamplerDiagnostics
kernelName(int) - Method in class jdistlib.inference.HybridSamplerDiagnostics
KernelTransition<S> - Class in jdistlib.inference: Immutable result of one reusable Markov transition.
KernelTransition(S, double[], double, IterationStats) - Constructor for class jdistlib.inference.KernelTransition
kind() - Method in class jdistlib.accelerator.ExecutionPlan
kind() - Method in class jdistlib.inference.CoordinateSupport
kind() - Method in class jdistlib.inference.ModelGraph.Node
kInvGoldRatio - Static variable in class jdistlib.math.Constants: This is the squared inverse of the golden ratio ((3 - sqrt(5.0))/ 2).
kl - Variable in class jdistlib.HyperGeometric.RandomState
kolmogorov_lilliefors_pvalue(double, int) - Static method in class jdistlib.disttest.NormalityTest
kolmogorov_lilliefors_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest: Exactly identical as kolmogorov_smirnov_statistic
kolmogorov_smirnov_pvalue(double, double[]) - Static method in class jdistlib.disttest.NormalityTest: Deprecated.
kolmogorov_smirnov_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest: Deprecated.
kolmogorov_smirnov_test(double[]) - Static method in class jdistlib.disttest.NormalityTest: Perform Kolmogorov-Smirnov two-sided normality test.
kolmogorov_smirnov_test(double[], double[]) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between two distribution, two-sided, exact p-value.
kolmogorov_smirnov_test(double[], double[], boolean) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between two distribution, two-sided.
kolmogorov_smirnov_test(double[], double[], TestKind) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between two distribution, exact p-value.
kolmogorov_smirnov_test(double[], double[], TestKind, boolean) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between two distribution.
kolmogorov_smirnov_test(double[], GenericDistribution) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between X and a known reference distribution, two-sided, exact p-value.
kolmogorov_smirnov_test(double[], GenericDistribution, boolean) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between X and a known reference distribution, two-sided.
kolmogorov_smirnov_test(double[], GenericDistribution, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between X and a known reference distribution, exact p-value.
kolmogorov_smirnov_test(double[], GenericDistribution, TestKind, boolean) - Static method in class jdistlib.disttest.DistributionTest: Compute the Kolmogorov-Smirnov test to test between X and a known reference distribution.
kr - Variable in class jdistlib.HyperGeometric.RandomState
kruskal_wallis_test(double[], int[]) - Static method in class jdistlib.disttest.DistributionTest: Kruskal-Wallis test
ks - Variable in class jdistlib.HyperGeometric.RandomState
Kumaraswamy - Class in jdistlib: Kumaraswamy distribution
Kumaraswamy(double, double) - Constructor for class jdistlib.Kumaraswamy

L

label() - Method in class jdistlib.inference.ModelGraph.Node
lambda - Variable in class jdistlib.Poisson
lamdl - Variable in class jdistlib.HyperGeometric.RandomState
lamdr - Variable in class jdistlib.HyperGeometric.RandomState
LANGUAGE_VERSION - Static variable in class jdistlib.inference.lang.ModelScript
languageVersion() - Method in class jdistlib.inference.lang.CompiledModelScript
Laplace - Class in jdistlib: Laplace distribution, from VGAM package
Laplace(double, double) - Constructor for class jdistlib.Laplace
largest - Variable in class jdistlib.evd.Extreme
largest - Variable in class jdistlib.evd.Order
last - Variable in class jdistlib.math.IntegrationResult
lbeta(double, double) - Static method in class jdistlib.math.MathFunctions
LbfgsOptimizer - Class in jdistlib.inference: Small deterministic L-BFGS maximizer intended for initialization and MAP fits.
lchoose(double, double) - Static method in class jdistlib.math.MathFunctions
ldexp(double, double) - Static method in class jdistlib.math.MathFunctions
ldexp(double, int) - Static method in class jdistlib.math.MathFunctions: Implementation of ldexp
leapfrogSteps() - Method in class jdistlib.inference.AdaptiveStaticHmcResult
leapfrogSteps() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
leapfrogSteps() - Method in class jdistlib.inference.IterationStats
leapfrogSteps() - Method in class jdistlib.inference.SamplingOptions
leapfrogSteps(int) - Method in class jdistlib.inference.SamplingOptions.Builder
LEFT - Enum constant in enum class jdistlib.accelerator.MatrixSide
LEFT_CENSORED - Enum constant in enum class jdistlib.finance.DistributionFit.Observation.Kind
leftCensored(double) - Static method in class jdistlib.finance.DistributionFit.Observation
leftInfinite(UnivariateFunction, long, DiscreteTailBound, CertifiedDiscreteOptions) - Static method in class jdistlib.CertifiedInfiniteDiscreteDistribution: Constructs support ..., start-1, start.
leftPowerLaw(double, double) - Static method in class jdistlib.DiscreteTailBounds: Left-tail integral-test bound for weights proportional to (-k + offset)^(-exponent).
leftSingularVectors() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition: Returns row-major thin U with shape rows by components.
leftSingularVectors() - Method in class jdistlib.accelerator.SingularValueDecomposition: Returns row-major thin U with shape rows by components.
Levy - Class in jdistlib
Levy() - Constructor for class jdistlib.Levy: Constructor for standard normal (i.e., mean = 0, sd = 1)
Levy(double, double) - Constructor for class jdistlib.Levy
LevyIncrementDistribution - Class in jdistlib.finance: Time-scaled increment of an infinitely-divisible transform-defined unit law.
LevyIncrementDistribution(TransformDistribution, double) - Constructor for class jdistlib.finance.LevyIncrementDistribution
LevyIncrementDistribution(TransformDistribution, double, FourierInversionOptions) - Constructor for class jdistlib.finance.LevyIncrementDistribution
lgamma1p(double) - Static method in class jdistlib.math.MathFunctions
lgammacor(double) - Static method in class jdistlib.math.MathFunctions
lgammafn(double) - Static method in class jdistlib.math.MathFunctions
lgammafn(double[]) - Static method in class jdistlib.math.MathFunctions: Batch call log gamma function
lgammafn_sign(double, int[]) - Static method in class jdistlib.math.MathFunctions
lgharmonic(int) - Static method in class jdistlib.math.MathFunctions
lgharmonic(int, double) - Static method in class jdistlib.math.MathFunctions
lgharmonic(int, double, double) - Static method in class jdistlib.math.MathFunctions: Calculate the log of generalized harmonic number
libraryVersion() - Method in class jdistlib.inference.RunManifest
License - Search tag in class jdistlib.rng.MersenneTwister: Section
License - Search tag in class jdistlib.rng.MersenneTwisterSafe: Section
likelihood(String, String[], ModelFactor) - Method in class jdistlib.inference.ModelBuilder: Adds a scalar likelihood factor and exposes it for pointwise predictive assessment.
likelihood(String, String, String[], ModelFactor) - Method in class jdistlib.inference.ModelBuilder: Adds a scalar likelihood factor with an explicit observation group.
likelihood(OptionObservation[], OptionInference.StatePriceModel, OptionInference.StateNoiseModel) - Static method in class jdistlib.finance.OptionInference
Lindley - Class in jdistlib: One-parameter Lindley lifetime distribution.
Lindley(double) - Constructor for class jdistlib.Lindley
line() - Method in class jdistlib.inference.lang.ScriptDiagnostic
LINE - Enum constant in enum class jdistlib.inference.ChartSpec.Type
linear(double, double[], double[], double, double) - Static method in class jdistlib.math.approx.ApproximationFunction: Linear approximation
LINEAR - Enum constant in enum class jdistlib.math.approx.ApproximationType
LinearAlgebraBackend - Interface in jdistlib.accelerator: Backend-neutral FP64 BLAS, sparse-BLAS, and reusable factorization surface.
LinearAlgebraOperation - Enum Class in jdistlib.accelerator: Backend-neutral operation identifiers used for capability and routing inspection.
linearCombination(double[]) - Method in class jdistlib.finance.MultivariateFinancialDistribution: Exact scalar law for a linear combination of the vector.
LinPack - Class in jdistlib.math: Routines that I took from LINPACK library.
LinPack() - Constructor for class jdistlib.math.LinPack
lmvgammafn(double, int) - Static method in class jdistlib.math.MathFunctions: Log of multivariate gamma function By: Roby Joehanes
lmvpsigammafn(double, int, int) - Static method in class jdistlib.math.PolyGamma: Log of multivariate psigamma function By: Roby Joehanes
LoadedGeneratedModel - Class in jdistlib.inference.lang: Closeable generated-model factory and its isolated class loader.
loc - Variable in class jdistlib.evd.Fretchet
loc - Variable in class jdistlib.evd.GeneralizedPareto
loc - Variable in class jdistlib.evd.GEV
loc - Variable in class jdistlib.evd.Gumbel
loc - Variable in class jdistlib.evd.ReverseWeibull
locate(ChainResult, BayesianModel) - Static method in class jdistlib.inference.Divergences
location - Variable in class jdistlib.Cauchy
location - Variable in class jdistlib.Laplace
location - Variable in class jdistlib.Logistic
log() - Method in class jdistlib.math.Complex
log(int) - Method in class jdistlib.inference.autodiff.ReverseTape
LOG - Enum constant in enum class jdistlib.accelerator.UnaryOperation
log_prod(double[]) - Static method in class jdistlib.math.VectorMath: Log of product of numbers.
log1p(int) - Method in class jdistlib.inference.autodiff.ReverseTape
LOG1P - Enum constant in enum class jdistlib.accelerator.UnaryOperation
log1pexp(double) - Static method in class jdistlib.math.MathFunctions
log1pmx(double) - Static method in class jdistlib.math.MathFunctions
log1px(double) - Static method in class jdistlib.math.MathFunctions: log1px takes a double and returns a double.
logAbsDeterminant() - Method in class jdistlib.accelerator.FloatLuFactor
logAbsDeterminant() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
logAbsDeterminant() - Method in class jdistlib.accelerator.LuFactor
logAbsDeterminant() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
logAbsJacobian() - Method in class jdistlib.inference.ReversibleJumpProposal
logAbsJacobian(ReversibleJumpState, double[], boolean) - Method in class jdistlib.inference.CoordinateInsertionTransformation
logAbsJacobian(ReversibleJumpState, double[], boolean) - Method in class jdistlib.inference.CoordinateSplitTransformation
logAbsJacobian(ReversibleJumpState, double[], boolean) - Method in interface jdistlib.inference.DimensionMatchingTransformation
logAcceptanceRatio() - Method in class jdistlib.inference.ReversibleJumpIterationStats
logAcceptanceRatio() - Method in class jdistlib.inference.SparseSubsetIterationStats
Logarithmic - Class in jdistlib
Logarithmic(double) - Constructor for class jdistlib.Logarithmic
logAtomWeights(UnivariateFunction) - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
logBesselK(double, double) - Static method in class jdistlib.finance.GeneralizedHyperbolicDistribution
logCharacteristic(double) - Method in class jdistlib.finance.CgmyDistribution
logCharacteristic(double) - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
logCharacteristic(double) - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
logCharacteristic(double) - Method in class jdistlib.finance.LevyIncrementDistribution
logCharacteristic(double) - Method in class jdistlib.finance.MeixnerDistribution
logCharacteristic(double) - Method in class jdistlib.finance.NormalTemperedStableDistribution
logCharacteristic(double) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
logCharacteristic(double) - Method in class jdistlib.finance.StableDistribution
logCharacteristic(double) - Method in interface jdistlib.finance.TransformDistribution
logCharacteristic(double) - Method in class jdistlib.finance.VarianceGammaDistribution
logCharacteristic(double) - Method in class jdistlib.Gamma
logCharacteristic(double) - Method in class jdistlib.Normal
logCharacteristic(double) - Method in class jdistlib.Poisson
logCharacteristic(double) - Method in class jdistlib.T
logCharacteristic(GenericDistribution, double) - Static method in class jdistlib.finance.DistributionTransforms
logDensities() - Method in class jdistlib.accelerator.LogisticRegressionBatchResult
logDensities() - Method in class jdistlib.inference.ChainResult
logDensities() - Method in class jdistlib.inference.ColumnarDraws
logDensity() - Method in class jdistlib.inference.ChainCheckpoint
logDensity() - Method in class jdistlib.inference.HybridKernelTransition
logDensity() - Method in class jdistlib.inference.KernelTransition
logDensity() - Method in class jdistlib.inference.RandomWalkKernel.State
logDensity(double[]) - Method in class jdistlib.BB1Copula
logDensity(double[]) - Method in class jdistlib.ClaytonCopula
logDensity(double[]) - Method in interface jdistlib.Copula: Natural logarithm of the copula density at an interior point.
logDensity(double[]) - Method in class jdistlib.CopulaDistribution: Natural logarithm of the joint density.
logDensity(double[]) - Method in class jdistlib.CVineCopula
logDensity(double[]) - Method in class jdistlib.DVineCopula
logDensity(double[]) - Method in class jdistlib.FrankCopula
logDensity(double[]) - Method in class jdistlib.GaussianCopula
logDensity(double[]) - Method in class jdistlib.GumbelCopula
logDensity(double[]) - Method in class jdistlib.IndependenceCopula
logDensity(double[]) - Method in class jdistlib.inference.BayesianModel
logDensity(double[]) - Method in interface jdistlib.inference.DifferentiableLogDensity
logDensity(double[]) - Method in class jdistlib.inference.EvaluationCounter
logDensity(double[]) - Method in interface jdistlib.inference.LogDensity
logDensity(double[]) - Method in class jdistlib.inference.ModelEvaluator
logDensity(double[]) - Method in interface jdistlib.inference.TemperedLogDensity
logDensity(double[]) - Method in class jdistlib.JoeCopula
logDensity(double[]) - Method in class jdistlib.RotatedCopula
logDensity(double[]) - Method in class jdistlib.StudentTCopula
logDensity(double, double) - Method in class jdistlib.PairCopula
logDensity(double, int, ReversibleJumpState) - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
logDensity(double, int, ReversibleJumpState) - Method in class jdistlib.inference.GaussianRjBirthProposal
logDensity(double, int, ReversibleJumpState) - Method in interface jdistlib.inference.RjBirthProposal
logDensity(double, int, SparseSubsetState) - Method in class jdistlib.inference.GaussianSparseCoefficientProposal
logDensity(double, int, SparseSubsetState) - Method in interface jdistlib.inference.SparseCoefficientProposal
logDensity(ModelState) - Method in interface jdistlib.inference.DifferentiableModelFactor
logDensity(ModelState) - Method in interface jdistlib.inference.ModelFactor
LogDensity - Interface in jdistlib.inference: An unnormalized log density on an unconstrained Euclidean state space.
logDensityAndAddGradient(ModelState, double[]) - Method in interface jdistlib.inference.DifferentiableModelFactor
logDensityAndGradient(double[], double[]) - Method in class jdistlib.inference.AcceleratedLogisticRegression
logDensityAndGradient(double[], double[]) - Method in class jdistlib.inference.autodiff.ReverseModeLogDensity
logDensityAndGradient(double[], double[]) - Method in class jdistlib.inference.BayesianModel
logDensityAndGradient(double[], double[]) - Method in interface jdistlib.inference.DifferentiableLogDensity: Evaluates the log density and replaces gradient with its gradient.
logDensityAndGradient(double[], double[]) - Method in class jdistlib.inference.EvaluationCounter
logDensityAndGradient(double[], double[]) - Method in class jdistlib.inference.ModelEvaluator
logDensityAndGradientBatch(double[][], double[], double[][]) - Method in class jdistlib.inference.AcceleratedLogisticRegression
logDensityAndGradientBatch(double[][], double[], double[][]) - Method in interface jdistlib.inference.BatchedDifferentiableLogDensity: Replaces every output row; implementations may execute the batch concurrently.
logDensityAt(int) - Method in class jdistlib.inference.ChainResult: Returns one retained log density without copying the chain.
logDensityEvaluations() - Method in class jdistlib.inference.EvaluationCounter
logDeterminant() - Method in class jdistlib.accelerator.CholeskyFactor: Returns the log determinant of the original SPD matrix.
logDeterminant() - Method in class jdistlib.accelerator.FloatCholeskyFactor
logDeterminant() - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
logDeterminant() - Method in interface jdistlib.accelerator.PreparedCholesky
logDeterminant() - Method in interface jdistlib.accelerator.PreparedFloatCholesky
logDeterminant() - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
logDeterminant() - Method in interface jdistlib.accelerator.PreparedSparseCholesky
logDeterminant() - Method in class jdistlib.accelerator.SparseCholeskyFactor
logDeterminantCumulative(double, double, double[][]) - Static method in class jdistlib.Wishart
logDeterminantCumulative(double, double, double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.Wishart: Computes P(log(det(W)) <= upper).
logDeterminantProbability(double, double, double, double[][]) - Static method in class jdistlib.Wishart
logDeterminantProbability(double, double, double, double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.Wishart: Computes P(lower <= log(det(W)) <= upper) without exponentiating the caller's thresholds, so extreme determinant events remain representable.
logForwardDensity() - Method in class jdistlib.inference.ReversibleJumpProposal
Logistic - Class in jdistlib
Logistic() - Constructor for class jdistlib.Logistic: Constructor for standard Logistic (location = 0, scale = 1)
Logistic(double, double) - Constructor for class jdistlib.Logistic
LOGISTIC - Enum constant in enum class jdistlib.accelerator.UnaryOperation
logisticRegression(double[][], double[], double[][], double) - Method in interface jdistlib.accelerator.ComputeBackend
logisticRegression(double[][], double[], double[][], double) - Method in class jdistlib.accelerator.CpuComputeBackend
LogisticRegressionBatchResult - Class in jdistlib.accelerator: Batched logistic-regression log densities and gradients.
LogisticRegressionBatchResult(double[], double[][]) - Constructor for class jdistlib.accelerator.LogisticRegressionBatchResult
LogitNormal - Class in jdistlib: Logit-normal distribution on the open unit interval.
LogitNormal(double, double) - Constructor for class jdistlib.LogitNormal
logJoint() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
logJoint() - Method in class jdistlib.inference.ReversibleJumpWithinModelTransition
logJoint() - Method in class jdistlib.inference.SparseSubsetCheckpoint
logJoint(double[], int[], double[]) - Method in interface jdistlib.inference.SparseSubsetLogJoint
logJoint(double[], int[], double[]) - Method in interface jdistlib.inference.SubsetLogJoint
logJoint(ReversibleJumpState) - Method in interface jdistlib.inference.ReversibleJumpTarget
logJoint(ReversibleJumpState) - Method in class jdistlib.inference.SubsetSelectionTarget
logJoint(SparseSubsetState) - Method in class jdistlib.inference.SparseSubsetTarget
logJointAt(int) - Method in class jdistlib.inference.ReversibleJumpResult
logJointAt(int) - Method in class jdistlib.inference.SparseSubsetResult
logJoints() - Method in class jdistlib.inference.ReversibleJumpResult
logJoints() - Method in class jdistlib.inference.SparseSubsetResult
logKernel(UnivariateFunction) - Method in class jdistlib.NumericalContinuousDistribution.Builder
logKernel(UnivariateFunction) - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
loglik(double, double, double, double) - Static method in class jdistlib.Tweedie
logLikelihood(double[][]) - Method in class jdistlib.MixedCopulaDistribution
logLikelihoodResult(double[][]) - Method in class jdistlib.MixedCopulaDistribution: Aggregates likelihood contributions while retaining row-level diagnostics.
logLikelihoodVariance() - Method in class jdistlib.inference.Waic.Result
LogLogistic - Class in jdistlib: Log logistic distribution.
LogLogistic(double, double) - Constructor for class jdistlib.LogLogistic
logMomentGenerating(double) - Method in class jdistlib.finance.CgmyDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.LevyIncrementDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.MeixnerDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.NormalTemperedStableDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.StableDistribution
logMomentGenerating(double) - Method in interface jdistlib.finance.TransformDistribution
logMomentGenerating(double) - Method in class jdistlib.finance.VarianceGammaDistribution
logMomentGenerating(double) - Method in class jdistlib.Gamma
logMomentGenerating(double) - Method in class jdistlib.Normal
logMomentGenerating(double) - Method in class jdistlib.Poisson
logMomentGenerating(double) - Method in class jdistlib.T
logMomentGenerating(GenericDistribution, double) - Static method in class jdistlib.finance.DistributionTransforms
LogNormal - Class in jdistlib
LogNormal() - Constructor for class jdistlib.LogNormal: Constructor for standard Logistic (location = 0, scale = 1)
LogNormal(double, double) - Constructor for class jdistlib.LogNormal
logProbability() - Method in class jdistlib.inference.SparseCandidateChoice
logProbability(int, SparseSubsetState, SparseSubsetTarget) - Method in class jdistlib.inference.ResidualInformedSparseCandidateProposal
logProbability(int, SparseSubsetState, SparseSubsetTarget) - Method in interface jdistlib.inference.SparseCandidateProposal
logProbability(int, SparseSubsetState, SparseSubsetTarget) - Method in class jdistlib.inference.UniformSparseCandidateProposal
logProposalDensity(double) - Method in interface jdistlib.RejectionEnvelope: Returns the normalized proposal log-density at x.
logProposalDensity(double) - Method in class jdistlib.UniformRejectionEnvelope
logReverseDensity() - Method in class jdistlib.inference.ReversibleJumpProposal
logScales() - Method in class jdistlib.inference.SparseSubsetCheckpoint
logspace_add(double, double) - Static method in class jdistlib.math.MathFunctions: Compute the log of a sum from logs of terms, i.e., log (exp (logx) + exp (logy)) without causing overflows and without throwing away large handfuls of accuracy.
logspace_sub(double, double) - Static method in class jdistlib.math.MathFunctions: Compute the log of a difference from logs of terms, i.e., log (exp (logx) - exp (logy)) without causing overflows and without throwing away large handfuls of accuracy.
logspace_sum(double[]) - Static method in class jdistlib.math.MathFunctions
logValue - Variable in class jdistlib.CopulaMeasureResult
logWeights() - Method in class jdistlib.inference.ParetoSmoothedImportanceSampling.Result
logWeights() - Method in class jdistlib.inference.PathfinderFit
logWeights(UnivariateFunction) - Method in class jdistlib.NumericalDiscreteDistribution.Builder
looic() - Method in class jdistlib.inference.PsisLoo.Result
LooModelComparison - Class in jdistlib.inference: Pointwise, paired comparison of models evaluated with PSIS-LOO.
LooModelComparison.Entry - Class in jdistlib.inference
LooModelComparison.NamedResult - Class in jdistlib.inference
LordPlusPlus - Class in jdistlib.disttest.online: Stateful LORD++ online-FDR controller for a prespecified hypothesis order.
LordPlusPlus(double, double, double[]) - Constructor for class jdistlib.disttest.online.LordPlusPlus
LOSS - Enum constant in enum class jdistlib.finance.RiskConvention
LOW_RANK_DIAGONAL - Enum constant in enum class jdistlib.inference.MetricConfiguration.Type
lower() - Method in class jdistlib.accelerator.CholeskyFactor: Returns a row-major copy of the lower-triangular factor.
lower() - Method in class jdistlib.accelerator.FloatCholeskyFactor
lower() - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
lower() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
lower() - Method in class jdistlib.accelerator.SparseCholeskyFactor: Returns the lower factor in permuted coordinates and one-based CSR storage.
lower() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
lower() - Method in class jdistlib.inference.CoordinateSupport
LOWER - Enum constant in enum class jdistlib.accelerator.MatrixTriangle
LOWER - Enum constant in enum class jdistlib.disttest.TestKind
LOWER - Enum constant in enum class jdistlib.finance.Tail
lowerBound - Variable in class jdistlib.math.opt.OptimizationConfig
lowerBound(double, int) - Static method in class jdistlib.inference.Constraints
lowerBound(int) - Method in interface jdistlib.finance.DistributionFit.ParametricFamily
lowerConcentration(Copula, double) - Static method in class jdistlib.finance.CopulaTailAnalysis
lowerQuantile() - Method in class jdistlib.inference.ParameterDiagnostics
lowerTailAsymptotic(double) - Method in class jdistlib.finance.StableDistribution: Leading left-tail probability for large positive distance from location.
lowerTailDependence(Copula) - Static method in class jdistlib.finance.CopulaTailAnalysis
lowRank() - Method in class jdistlib.inference.MetricConfiguration
lowRankDiagonal(int) - Static method in class jdistlib.inference.MetricConfiguration
LuFactor - Class in jdistlib.accelerator: Immutable FP64 partial-pivoted LU factorization of a square matrix.
LuFactor(int, double[], int[], int) - Constructor for class jdistlib.accelerator.LuFactor: Creates a factor where row i came from original row permutation[i].

M

m - Variable in class jdistlib.Ansari
m - Variable in class jdistlib.Binomial.RandomState
m - Variable in class jdistlib.HyperGeometric.RandomState
m - Variable in class jdistlib.Nakagami
m - Variable in class jdistlib.Wilcoxon
M_1_PI - Static variable in class jdistlib.math.Constants
M_1_SQRT_2 - Static variable in class jdistlib.math.Constants
M_1_SQRT_2PI - Static variable in class jdistlib.math.Constants
M_2PI - Static variable in class jdistlib.math.Constants
M_LN_2PI - Static variable in class jdistlib.math.Constants
M_LN_SQRT_2PI - Static variable in class jdistlib.math.Constants
M_LN_SQRT_PI - Static variable in class jdistlib.math.Constants
M_LN_SQRT_PId2 - Static variable in class jdistlib.math.Constants
M_LN10 - Static variable in class jdistlib.math.Constants
M_LN2 - Static variable in class jdistlib.math.Constants
M_LOG_PI - Static variable in class jdistlib.math.Constants
M_LOG10_2 - Static variable in class jdistlib.math.Constants
M_PI - Static variable in class jdistlib.math.Constants
M_PI_2 - Static variable in class jdistlib.math.Constants
M_PI_4 - Static variable in class jdistlib.math.Constants
M_PISQ_8 - Static variable in class jdistlib.math.Constants
M_SQRT_2 - Static variable in class jdistlib.math.Constants
M_SQRT_2dPI - Static variable in class jdistlib.math.Constants
M_SQRT_32 - Static variable in class jdistlib.math.Constants
M_SQRT_PI - Static variable in class jdistlib.math.Constants
mad(double[]) - Static method in class jdistlib.math.VectorMath: Compute the Median Absolute Deviation (MAD) (i.e., median(abs(e - median(e))))
main(String[]) - Static method in class jdistlib.disttest.DistributionTest
main(String[]) - Static method in class jdistlib.inference.lang.ModelScriptCli
main(String[]) - Static method in class jdistlib.math.density.Density
main(String[]) - Static method in class jdistlib.math.opt.Bobyqa
main(String[]) - Static method in class jdistlib.math.opt.Optimization
main(String[]) - Static method in class jdistlib.math.Polynomial
main(String[]) - Static method in class jdistlib.rng.MersenneTwisterSafe: Tests the code.
main(String[]) - Static method in class jdistlib.Spearman
Makeham - Class in jdistlib: Makeham survival distribution with scale, shape, and constant hazard.
Makeham(double, double, double) - Constructor for class jdistlib.Makeham
manifest() - Method in class jdistlib.inference.Fit
mann_whitney_u_test(double[], double[], double, boolean, boolean, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Mann-Whitney-U test
mann_whitney_u_test(double[], double[], double, boolean, boolean, TestKind, double, double) - Static method in class jdistlib.disttest.DistributionTest: Mann-Whitney-Wilcoxon test with the same rank rounding controls as current R.
ManyShortChains - Class in jdistlib.inference: Deterministic many-short-chain execution using common-initialization superchains.
ManyShortChainsResult - Class in jdistlib.inference: Results and nested convergence diagnostics from a superchain design.
MappedDrawStore - Class in jdistlib.inference: Fixed-capacity selected-coordinate draw sink and zero-copy memory-mapped reader.
MappedDrawStore(Path, int[], int) - Constructor for class jdistlib.inference.MappedDrawStore
marginalScale() - Method in class jdistlib.inference.PathfinderResult
marginalTransforms(double[][], long, CopulaMarginal...) - Static method in class jdistlib.CopulaFitter: Applies a reproducible randomized distributional transform.
marginalTransforms(double[][], CopulaMarginal...) - Static method in class jdistlib.CopulaFitter: Applies marginal probability transforms.
marginalTransforms(double[][], RandomEngine, CopulaMarginal...) - Static method in class jdistlib.CopulaFitter: Applies marginal probability transforms.
mark() - Method in class jdistlib.inference.autodiff.ReverseTape: Returns a mark to which temporary nodes can later be rewound.
massScaling() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
match(double[], double[]) - Static method in class jdistlib.util.Utilities: Mimic the behavior of match function in R.
match(int[], int[]) - Static method in class jdistlib.util.Utilities
match(S[], S[]) - Static method in class jdistlib.util.Utilities
MathFunctions - Class in jdistlib.math
MathFunctions() - Constructor for class jdistlib.math.MathFunctions
MatrixDiagonal - Enum Class in jdistlib.accelerator: Whether a triangular matrix stores or implies its diagonal.
matrixMultiply(double[][], double[][]) - Method in interface jdistlib.accelerator.ComputeBackend
matrixMultiply(double[][], double[][]) - Method in class jdistlib.accelerator.CpuComputeBackend
MatrixSide - Enum Class in jdistlib.accelerator: Side on which a triangular matrix operates.
MatrixTranspose - Enum Class in jdistlib.accelerator: Transposition applied to a row-major dense matrix operand.
MatrixTriangle - Enum Class in jdistlib.accelerator: Stored triangle of a triangular matrix.
max(double[]) - Static method in class jdistlib.math.VectorMath
MAX - Enum constant in enum class jdistlib.util.Utilities.RankTies
MAX_EVALUATIONS_REACHED - Enum constant in enum class jdistlib.MultivariateProbabilityStatus: A usable estimate was produced, but its error estimate exceeds tolerance.
MAX_EVALUATIONS_REACHED - Static variable in class jdistlib.MultivariateProbabilityResult: Legacy integer code corresponding to MultivariateProbabilityStatus.MAX_EVALUATIONS_REACHED.
maxCallbackTime(long, TimeUnit) - Method in class jdistlib.math.IntegrationOptions.Builder: Sets a benchmark-oriented wall-clock limit for one callback evaluation.
maxdev(double[]) - Static method in class jdistlib.math.VectorMath: Maximum deviation (i.e., max(abs(e - median(e))))
maxEvaluations - Variable in class jdistlib.MultivariateProbabilityOptions
maxEvaluations(int) - Method in class jdistlib.math.IntegrationOptions.Builder
maximize(DifferentiableLogDensity, double[], int, int, double) - Static method in class jdistlib.inference.LbfgsOptimizer
maximum(GenericDistribution, int) - Static method in class jdistlib.finance.OrderStatisticDistribution
MAXIMUM_LIKELIHOOD - Enum constant in enum class jdistlib.CopulaFitOptions.Method
MAXIMUM_SUBDIVISIONS - Enum constant in enum class jdistlib.math.IntegrationStatus
maximumAbsoluteError() - Method in class jdistlib.inference.GradientCheckResult
maximumActive() - Method in class jdistlib.inference.SparseSubsetTarget
maximumChunks() - Method in class jdistlib.inference.PrecisionGoal
maximumChunks(int) - Method in class jdistlib.inference.PrecisionGoal.Builder
maximumConstraintError() - Method in class jdistlib.inference.solver.HigherIndexDaeSolver.Result
maximumDrawdown(GenericDistribution, int, int, long) - Static method in class jdistlib.finance.PathFunctionalDistributions
maximumEnergyError() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
maximumEnergyError() - Method in class jdistlib.inference.SamplingOptions
maximumEnergyError(double) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
maximumEnergyError(double) - Method in class jdistlib.inference.SamplingOptions.Builder
maximumIterations - Variable in class jdistlib.inference.solver.AlgebraicSolver.Options
maximumIterations() - Method in class jdistlib.inference.PathfinderOptions
maximumIterations(int) - Method in class jdistlib.inference.PathfinderOptions.Builder
maximumLeapfrogSteps() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
maximumLeapfrogSteps() - Method in class jdistlib.inference.AdjustedMclmcTuningOptions
maximumLeapfrogSteps(int) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
maximumLeapfrogSteps(int) - Method in class jdistlib.inference.AdjustedMclmcTuningOptions.Builder
maximumLikelihood(DistributionFit.Observation[], DistributionFit.ParametricFamily, double[]) - Static method in class jdistlib.finance.DistributionFit
maximumMeanKl() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Result
maximumNodes(int) - Method in class jdistlib.CdfTableOptions.Builder
maximumRelativeError() - Method in class jdistlib.inference.GradientCheckResult
maximumSliceSteps() - Method in class jdistlib.inference.SamplingOptions
maximumSliceSteps(int) - Method in class jdistlib.inference.SamplingOptions.Builder
maximumSteps - Variable in class jdistlib.inference.solver.OdeSolver.Options
maximumSteps - Variable in class jdistlib.inference.solver.StiffOdeSolver.Options
maximumTerms(int) - Method in class jdistlib.CertifiedDiscreteOptions.Builder
maximumTreeDepth() - Method in class jdistlib.inference.SamplerDiagnostics
maximumTreeDepth() - Method in class jdistlib.inference.SamplingOptions
maximumTreeDepth(int) - Method in class jdistlib.inference.SamplingOptions.Builder
maxjx - Variable in class jdistlib.HyperGeometric.RandomState
maxNumFunctionCall - Variable in class jdistlib.math.opt.OptimizationConfig
maxTotalTime(long, TimeUnit) - Method in class jdistlib.math.IntegrationOptions.Builder: Sets a benchmark-oriented total wall-clock budget.
Maxwell - Class in jdistlib: Maxwell distribution using VGAM's positive rate parameterization.
Maxwell(double) - Constructor for class jdistlib.Maxwell
MaxwellBoltzmann - Class in jdistlib: Maxwell-Boltzmann speed distribution using the conventional scale sigma, the common standard deviation of three independent centered normal coordinates.
MaxwellBoltzmann(double) - Constructor for class jdistlib.MaxwellBoltzmann
McmcDiagnosticReport - Class in jdistlib.inference: Immutable parameter and sampler diagnostics with machine-readable output.
McmcDiagnostics - Class in jdistlib.inference: Rank-normalized R-hat, bulk/tail ESS, MCSE, and sampler diagnostics.
McmcJson - Class in jdistlib.inference: Dependency-free versioned JSON serialization for inference diagnostics.
mCoefficients - Variable in class jdistlib.math.Polynomial
mCoefficients - Variable in class jdistlib.math.spline.SmoothSplineResult
mCompromise - Variable in class jdistlib.math.approx.ApproximationFunction
mCriterion - Variable in class jdistlib.math.spline.SmoothSplineResult
mcse() - Method in class jdistlib.inference.PrecisionContinuationResult
mCVScore - Variable in class jdistlib.math.spline.SmoothSplineResult
ME_DOMAIN - Static variable in class jdistlib.math.Constants
ME_NOCONV - Static variable in class jdistlib.math.Constants
ME_NONE - Static variable in class jdistlib.math.Constants
ME_PRECISION - Static variable in class jdistlib.math.Constants
ME_RANGE - Static variable in class jdistlib.math.Constants
ME_UNDERFLOW - Static variable in class jdistlib.math.Constants
mean() - Method in interface jdistlib.inference.GaussianReference
mean() - Method in class jdistlib.inference.ParameterDiagnostics
mean() - Method in class jdistlib.inference.ReversibleJumpParameterSummary
mean(double[]) - Static method in class jdistlib.math.VectorMath
mean(int) - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
meanAcceptanceProbability() - Method in class jdistlib.inference.SamplerDiagnostics
meanAcceptanceProbability() - Method in class jdistlib.inference.WarmupResult
meanKl() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Step
meanlog - Variable in class jdistlib.LogNormal
meanMcse(double[]) - Static method in class jdistlib.inference.MonteCarloError
meanNanoseconds() - Method in class jdistlib.inference.FactorProfile
measure(double[]) - Method in class jdistlib.MixedCopulaDistribution: Evaluates density, probability mass, or mixed product-measure density.
MEASURE_FAILURE - Enum constant in enum class jdistlib.CopulaLogLikelihoodResult.Status
median() - Method in class jdistlib.inference.ParameterDiagnostics
median(double[]) - Static method in class jdistlib.math.VectorMath: Get the median
MeixnerDistribution - Class in jdistlib.finance: Meixner return law in the (scale, skew, shape, location) parameterization.
MeixnerDistribution(double, double, double, double) - Constructor for class jdistlib.finance.MeixnerDistribution
MeixnerDistribution(double, double, double, double, FourierInversionOptions) - Constructor for class jdistlib.finance.MeixnerDistribution
member(int) - Method in class jdistlib.inference.lang.TupleValue: Returns the one-based member used by Stan tuple syntax.
MersenneTwister - Class in jdistlib.rng: MersenneTwister and MersenneTwisterFast
MersenneTwister() - Constructor for class jdistlib.rng.MersenneTwister: Constructor using the default seed.
MersenneTwister(int[]) - Constructor for class jdistlib.rng.MersenneTwister: Constructor using an array of integers as seed.
MersenneTwister(long) - Constructor for class jdistlib.rng.MersenneTwister: Constructor using a given seed.
MersenneTwister and MersenneTwisterFast - Search tag in class jdistlib.rng.MersenneTwister: Section
MersenneTwister and MersenneTwisterFast - Search tag in class jdistlib.rng.MersenneTwisterSafe: Section
MersenneTwisterSafe - Class in jdistlib.rng: MersenneTwister and MersenneTwisterFast
MersenneTwisterSafe() - Constructor for class jdistlib.rng.MersenneTwisterSafe: Constructor using the default seed.
MersenneTwisterSafe(int[]) - Constructor for class jdistlib.rng.MersenneTwisterSafe: Constructor using an array of integers as seed.
MersenneTwisterSafe(long) - Constructor for class jdistlib.rng.MersenneTwisterSafe: Constructor using a given seed.
message() - Method in class jdistlib.CopulaFitResult
message() - Method in class jdistlib.CopulaLikelihoodDiagnostics
message() - Method in class jdistlib.CopulaLogLikelihoodResult
message() - Method in class jdistlib.CopulaMeasureResult
message() - Method in class jdistlib.inference.GradientCheckResult
message() - Method in class jdistlib.inference.lang.ScriptDiagnostic
message() - Method in class jdistlib.math.ImmutableIntegrationResult
message() - Method in class jdistlib.math.IntegrationResult
message() - Method in class jdistlib.math.IntegrationStabilityResult: Returns a concise human-readable assessment.
message() - Method in class jdistlib.MultivariateProbabilityResult
message() - Method in enum class jdistlib.MultivariateProbabilityStatus: Human-readable status text.
message() - Method in class jdistlib.VineFitResult
mEstimatedDF - Variable in class jdistlib.math.spline.SmoothSplineResult
metadata() - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
metadata() - Method in class jdistlib.inference.PsisLoo.Result
metadata() - Method in class jdistlib.inference.Waic.Result
method(IntegrationOptions.Method) - Method in class jdistlib.math.IntegrationOptions.Builder
metric() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
metric(MetricConfiguration) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
metric(MetricConfiguration) - Method in class jdistlib.inference.SamplingOptions.Builder
metricConditionNumber() - Method in class jdistlib.inference.IterationStats: Approximate condition number of the active inverse metric, when reported.
metricConditionNumber() - Method in class jdistlib.inference.WarmupTrace.Entry
metricConfiguration() - Method in class jdistlib.inference.SamplingOptions
MetricConfiguration - Class in jdistlib.inference: Immutable Euclidean metric selection for HMC-family samplers.
MetricConfiguration.Type - Enum Class in jdistlib.inference
MetropolisAdjustedLangevin - Class in jdistlib.inference: Metropolis-adjusted Langevin sampler with dual-averaged proposal scale.
MetropolisAdjustedLangevin() - Constructor for class jdistlib.inference.MetropolisAdjustedLangevin
MetropolisBlockKernel - Class in jdistlib.inference: Gaussian random-walk update for a declared continuous or discrete state block.
MetropolisBlockKernel(int[], double, boolean) - Constructor for class jdistlib.inference.MetropolisBlockKernel
mF - Variable in class jdistlib.math.opt.OptimizationResult
mFitCVScore - Variable in class jdistlib.math.spline.SmoothSplineResult
mHasFactorizationProblems - Variable in class jdistlib.math.spline.SmoothSplineResult
mHi - Variable in class jdistlib.math.approx.ApproximationFunction
midhinge(double[]) - Static method in class jdistlib.math.VectorMath: Mid hinge.
midrange(double[]) - Static method in class jdistlib.math.VectorMath: Mid-range of e (i.e., (max(e) + min(e)) / 2)
min(double[]) - Static method in class jdistlib.math.VectorMath
MIN - Enum constant in enum class jdistlib.util.Utilities.RankTies
minimum(GenericDistribution, int) - Static method in class jdistlib.finance.OrderStatisticDistribution
MINIMUM_DEGREE - Enum constant in enum class jdistlib.accelerator.SparseOrdering: Greedily eliminate the active vertex with minimum graph degree.
minimumDraws() - Method in class jdistlib.inference.PrecisionGoal
minimumDraws(int) - Method in class jdistlib.inference.PrecisionGoal.Builder
minimumMoveWeight() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
minimumMoveWeight() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
minimumMoveWeight(double) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
minimumMoveWeight(double) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
minimumProbability() - Method in class jdistlib.inference.ShrinkageSelection.Result
minimumTerms(int) - Method in class jdistlib.CertifiedDiscreteOptions.Builder
minjx - Variable in class jdistlib.HyperGeometric.RandomState
minus(Polynomial) - Method in class jdistlib.math.Polynomial: Subtract another polynomial from this polynomial and store the result into a new instance of QPolynomial
minusEquals(Polynomial) - Method in class jdistlib.math.Polynomial: Subtract another polynomial from this polynomial, in place (this = this - poly)
mIterNo - Variable in class jdistlib.math.spline.SmoothSplineResult
MixedCopulaDistribution - Class in jdistlib: Joint distribution with continuous, discrete, or mixed scalar marginals.
MixedCopulaDistribution(Copula, CopulaMarginal...) - Constructor for class jdistlib.MixedCopulaDistribution
MixedCopulaDistribution(Copula, CopulaMeasureOptions, CopulaMarginal...) - Constructor for class jdistlib.MixedCopulaDistribution
MixedStateSpace - Class in jdistlib.inference: Coordinate-by-coordinate support declaration for hybrid MCMC.
MixedStateSpace(CoordinateSupport...) - Constructor for class jdistlib.inference.MixedStateSpace
mixture(double[], GenericDistribution...) - Static method in class jdistlib.Distributions
MixtureDistribution - Class in jdistlib: Normalized finite mixture of scalar distribution objects.
MixtureDistribution(double[], GenericDistribution...) - Constructor for class jdistlib.MixtureDistribution
mKnots - Variable in class jdistlib.math.spline.SmoothSplineResult
mLambda - Variable in class jdistlib.math.spline.SmoothSplineResult
mlen - Variable in class jdistlib.evd.Extreme
mlen - Variable in class jdistlib.evd.Order
mLeverage - Variable in class jdistlib.math.spline.SmoothSplineResult
mLo - Variable in class jdistlib.math.approx.ApproximationFunction
mode() - Method in class jdistlib.inference.PathfinderResult
mode() - Method in class jdistlib.NumericalContinuousDistribution: Returns the best mode observed by transformed-grid search and refinement.
mode() - Method in class jdistlib.NumericalDiscreteDistribution: Returns the smallest outcome having maximum mass.
model() - Method in class jdistlib.inference.lang.CompiledModelScript
model(String, PsisLoo.Result) - Static method in class jdistlib.inference.LooModelComparison
ModelBuilder - Class in jdistlib.inference: Fluent builder for named constrained parameters and model factors.
ModelBuilder() - Constructor for class jdistlib.inference.ModelBuilder
modelChanges() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
ModelCompilationCache - Class in jdistlib.inference.lang: Validated on-disk compilation cache for generated model wrappers.
modelCount() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
ModelData - Class in jdistlib.inference: Immutable named numeric data supplied to a model.
modelEffectiveSampleSizes() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
ModelEvaluationCache - Class in jdistlib.inference: Cached per-factor values for proposal algorithms that change few coordinates.
ModelEvaluationCache(BayesianModel) - Constructor for class jdistlib.inference.ModelEvaluationCache
ModelEvaluator - Class in jdistlib.inference: Non-thread-safe allocation-free evaluator intended for one sampler chain.
ModelFactor - Interface in jdistlib.inference: One prior, likelihood, or constraint contribution to a model log density.
ModelFactors - Class in jdistlib.inference: Analytic common priors and likelihood factors for the programmatic builder.
modelFingerprint() - Method in class jdistlib.inference.PortableCheckpoint
modelFingerprint() - Method in class jdistlib.inference.PortableReversibleJumpCheckpoint
modelFingerprint() - Method in class jdistlib.inference.PortableSparseSubsetCheckpoint
modelFingerprint() - Method in class jdistlib.inference.WarmupBundle
ModelGraph - Class in jdistlib.inference: Immutable bipartite parameter/factor graph for inspection and rendering.
ModelGraph.Edge - Class in jdistlib.inference
ModelGraph.Node - Class in jdistlib.inference
ModelGraph.NodeKind - Enum Class in jdistlib.inference
ModelGraphExport - Class in jdistlib.inference: Graphviz DOT and versioned JSON export for model dependency graphs.
modelHash() - Method in class jdistlib.inference.RunManifest
modelId() - Method in class jdistlib.inference.ReversibleJumpModelSpace
modelId() - Method in class jdistlib.inference.ReversibleJumpState
modelIds() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
modelKey() - Method in class jdistlib.inference.SparseSubsetState: Canonical collision-free textual identity used by sparse model reports.
modelMcses() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
modelName(long) - Method in class jdistlib.inference.SubsetSelectionTarget
modelName(SparseSubsetState) - Method in class jdistlib.inference.SparseSubsetTarget
modelNames() - Method in class jdistlib.inference.PredictiveStacking.Result
modelProbabilities() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
modelRHats() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
ModelScript - Class in jdistlib.inference.lang: Java-native compiler for the JDistlib language and its Stan-compatible source core.
ModelScriptCli - Class in jdistlib.inference.lang: Minimal ahead-of-time source-generation CLI for Gradle and shell workflows.
ModelScriptException - Exception Class in jdistlib.inference.lang: Parse, validation, or compilation failure with source diagnostics.
ModelScriptException(List<ScriptDiagnostic>) - Constructor for exception class jdistlib.inference.lang.ModelScriptException
modelSizeCounts() - Method in class jdistlib.inference.SparseSubsetCheckpoint
modelSizeProbability(int) - Method in class jdistlib.inference.SparseSubsetSummary
ModelSourceGenerator - Class in jdistlib.inference.lang: Ahead-of-time Java source generation for a validated embedded model script.
modelSpace(long) - Method in interface jdistlib.inference.ReversibleJumpTarget
modelSpace(long) - Method in class jdistlib.inference.SubsetSelectionTarget
ModelSpecificRjKernel - Class in jdistlib.inference: Dispatches to a distinct within-model kernel for each declared model identifier.
ModelSpecificRjKernel(String, Map<Long, ReversibleJumpWithinModelKernel>) - Constructor for class jdistlib.inference.ModelSpecificRjKernel
ModelState - Class in jdistlib.inference: Read-only named view of one constrained model state and its observed data.
modelVisits() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
MomentAnalysisOptions - Class in jdistlib: Immutable settings for absolute-moment diagnostics.
MomentAnalysisOptions.Builder - Class in jdistlib: Builder for moment orders and the left/right reporting boundary.
momentExists(double) - Method in class jdistlib.finance.StableDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.CgmyDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.LevyIncrementDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.MeixnerDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.NormalTemperedStableDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.StableDistribution
momentGeneratingDomain() - Method in interface jdistlib.finance.TransformDistribution
momentGeneratingDomain() - Method in class jdistlib.finance.VarianceGammaDistribution
momentGeneratingDomain() - Method in class jdistlib.Gamma
momentGeneratingDomain() - Method in class jdistlib.Normal
momentGeneratingDomain() - Method in class jdistlib.Poisson
momentGeneratingDomain() - Method in class jdistlib.T
MonotoneTransformDistribution - Class in jdistlib: Distribution induced by a differentiable, strictly monotone transformation.
MonotoneTransformDistribution(GenericDistribution, UnivariateFunction, UnivariateFunction, UnivariateFunction, boolean, double, double) - Constructor for class jdistlib.MonotoneTransformDistribution
MonteCarloError - Class in jdistlib.inference: MCSE and efficiency helpers for one stationary retained sequence.
monteCarloStandardError() - Method in class jdistlib.inference.ParameterDiagnostics
mood_test(double[], double[]) - Static method in class jdistlib.disttest.DistributionTest: Performs Mood's two-sample test for a difference in scale parameters.
mood_test(double[], double[], TestKind) - Static method in class jdistlib.disttest.DistributionTest: Performs Mood's two-sample test for a difference in scale parameters.
move() - Method in class jdistlib.inference.ReversibleJumpIterationStats
move() - Method in class jdistlib.inference.SparseSubsetIterationStats
moveAcceptanceRate(int) - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
moveAcceptanceRate(int) - Method in class jdistlib.inference.ReversibleJumpResult
moveAccepts() - Method in class jdistlib.inference.SparseSubsetCheckpoint
moveAccepts(int) - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
moveAccepts(int) - Method in class jdistlib.inference.ReversibleJumpResult
moveAttempts() - Method in class jdistlib.inference.SparseSubsetCheckpoint
moveAttempts(int) - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
moveAttempts(int) - Method in class jdistlib.inference.ReversibleJumpResult
moveCount() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
moveCount() - Method in class jdistlib.inference.ReversibleJumpResult
moveName(int) - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
moveName(int) - Method in class jdistlib.inference.ReversibleJumpResult
moveNames() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
moveNames() - Method in class jdistlib.inference.SparseSubsetCheckpoint
moveWeights() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
moveWeights() - Method in class jdistlib.inference.SparseSubsetCheckpoint
mPenalizedCriterion - Variable in class jdistlib.math.spline.SmoothSplineResult
mSeed - Variable in class jdistlib.rng.RandomEngine
mSmoothedValues - Variable in class jdistlib.math.spline.SmoothSplineResult
mSmoothingParameter - Variable in class jdistlib.math.spline.SmoothSplineResult
mType - Variable in class jdistlib.math.approx.ApproximationFunction
mu - Variable in class jdistlib.BetaBinomial
mu - Variable in class jdistlib.InvNormal
mu - Variable in class jdistlib.Levy
mu - Variable in class jdistlib.Logarithmic
mu - Variable in class jdistlib.Normal
mu - Variable in class jdistlib.Tweedie
Multinomial - Class in jdistlib: Multinomial mass and random generation for a vector of category counts.
MultipleTesting - Class in jdistlib.disttest: Multiple-testing adjustments and Storey q-values.
MultipleTesting.AdaptiveFdrResult - Class in jdistlib.disttest: Result of the level-dependent two-stage BKY procedure.
MultipleTesting.CensoredTestResult - Class in jdistlib.disttest: Result for a family whose unrecorded p-values are known to exceed a limit.
MultipleTesting.GroupedFdrResult - Class in jdistlib.disttest: Result of the two-level Benjamini-Bogomolov grouped procedure.
MultipleTesting.Method - Enum Class in jdistlib.disttest: Supported p-value adjustment procedures.
MultipleTesting.StepDownFdrResult - Class in jdistlib.disttest: Result of a level-dependent step-down FDR procedure.
multiply(double[]) - Method in class jdistlib.matrix.CsrMatrix: Multiplies this sparse matrix by a dense vector.
multiply(double[][]) - Method in interface jdistlib.accelerator.PreparedTransposeProduct: Multiplies the transpose of the prepared matrix by one or more row vectors.
multiply(double, double[], double, double[]) - Method in interface jdistlib.accelerator.PreparedCsrMatrix: Performs y := alpha*A*x + beta*y.
multiply(double, double[], int, double, double[]) - Method in interface jdistlib.accelerator.PreparedCsrMatrix: Performs C := alpha*A*B + beta*C for row-major dense matrices.
multiply(float, float[], float, float[]) - Method in interface jdistlib.accelerator.PreparedFloatCsrMatrix
multiply(float, float[], int, float, float[]) - Method in interface jdistlib.accelerator.PreparedFloatCsrMatrix
multiply(int, double) - Method in class jdistlib.inference.autodiff.ReverseTape
multiply(int, int) - Method in class jdistlib.inference.autodiff.ReverseTape
multiply(MatrixTranspose, double, double[], int, double, double[]) - Method in interface jdistlib.accelerator.PreparedDenseMatrix: Performs C := alpha*op(A)*B + beta*C with row-major B and C.
multiply(MatrixTranspose, float, float[], int, float, float[]) - Method in interface jdistlib.accelerator.PreparedFloatDenseMatrix
multiply(Complex) - Method in class jdistlib.math.Complex
multiplyBatched(MatrixTranspose, double, double[][], int, double, double[][]) - Method in interface jdistlib.accelerator.PreparedDenseMatrix
multiplyBatched(MatrixTranspose, float, float[][], int, float, float[][]) - Method in interface jdistlib.accelerator.PreparedFloatDenseMatrix
MultivariableFunction - Interface in jdistlib.math: Abstraction of a function with multiple parameters
MultivariateCauchy - Class in jdistlib: Multivariate Cauchy distribution, the multivariate Student t law with one df.
MultivariateFinancialDistribution - Class in jdistlib.finance: Multivariate GH/NIG/VG, symmetric stable, or normal-tempered-stable construction.
MultivariateHypergeometric - Class in jdistlib: Sampling without replacement from multiple population categories.
MultivariateLaplace - Class in jdistlib: Symmetric multivariate Laplace law defined as a normal-exponential mixture.
MultivariateLogNormal - Class in jdistlib: Component-wise exponential transform of a multivariate normal vector.
MultivariateNormal - Class in jdistlib: Multivariate normal density and random generation using a covariance matrix.
MultivariateOptimization - Class in jdistlib.math.opt
MultivariateOptimization() - Constructor for class jdistlib.math.opt.MultivariateOptimization
MultivariatePowerExponential - Class in jdistlib: Elliptical multivariate power-exponential (generalized Gaussian) law.
MultivariateProbabilityOptions - Class in jdistlib: Accuracy and work limits for randomized multivariate probability integration.
MultivariateProbabilityOptions() - Constructor for class jdistlib.MultivariateProbabilityOptions: Uses 12 randomized replications and at most 131072 evaluations.
MultivariateProbabilityOptions(double, double, int, int) - Constructor for class jdistlib.MultivariateProbabilityOptions
MultivariateProbabilityResult - Class in jdistlib: Result of a numerical multivariate probability calculation.
MultivariateProbabilityStatus - Enum Class in jdistlib: Terminal status of a numerical multivariate probability calculation.
MultivariateStudentT - Class in jdistlib: Elliptical multivariate Student t distribution.
mX - Variable in class jdistlib.math.approx.ApproximationFunction
mX - Variable in class jdistlib.math.opt.OptimizationResult
mXMax - Variable in class jdistlib.math.spline.SmoothSplineResult
mXMin - Variable in class jdistlib.math.spline.SmoothSplineResult
mY - Variable in class jdistlib.math.approx.ApproximationFunction

N

n - Variable in class jdistlib.Ansari
n - Variable in class jdistlib.Binomial
n - Variable in class jdistlib.HyperGeometric
n - Variable in class jdistlib.Kendall
n - Variable in class jdistlib.SignRank
n - Variable in class jdistlib.Spearman
n - Variable in class jdistlib.Wilcoxon
N - Variable in class jdistlib.Zipf
n1 - Variable in class jdistlib.HyperGeometric.RandomState
n1s - Variable in class jdistlib.HyperGeometric.RandomState
n2 - Variable in class jdistlib.HyperGeometric.RandomState
n2s - Variable in class jdistlib.HyperGeometric.RandomState
NA - Enum constant in enum class jdistlib.util.Bool3
Nakagami - Class in jdistlib
Nakagami(double, double) - Constructor for class jdistlib.Nakagami
name() - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
name() - Method in class jdistlib.inference.ChartSpec.Series
name() - Method in class jdistlib.inference.ContinuousBlockMetropolisKernel
name() - Method in class jdistlib.inference.DiscreteMetropolisKernel
name() - Method in class jdistlib.inference.FactorProfile
name() - Method in class jdistlib.inference.FactorSpec
name() - Method in class jdistlib.inference.FiniteDiscreteGibbsKernel
name() - Method in class jdistlib.inference.FixedDimensionSamplerRjKernel
name() - Method in interface jdistlib.inference.GeneratedQuantity
name() - Method in interface jdistlib.inference.HybridKernel
name() - Method in class jdistlib.inference.LooModelComparison.Entry
name() - Method in class jdistlib.inference.ModelSpecificRjKernel
name() - Method in class jdistlib.inference.ParameterDiagnostics
name() - Method in class jdistlib.inference.ParameterSpec
name() - Method in class jdistlib.inference.ReversibleJumpModelSpace
name() - Method in interface jdistlib.inference.ReversibleJumpMove
name() - Method in class jdistlib.inference.ReversibleJumpParameterSummary
name() - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
name() - Method in class jdistlib.inference.ShrinkageSelection.Variable
name() - Method in class jdistlib.inference.SubsetBirthMove
name() - Method in class jdistlib.inference.SubsetDeathMove
name() - Method in class jdistlib.inference.SubsetSwapMove
name(int) - Method in class jdistlib.inference.ObservationMetadata
named(BayesianModel, Map<String, double[]>) - Static method in class jdistlib.inference.InitialStates
names() - Method in class jdistlib.inference.GeneratedQuantitySink
names() - Method in class jdistlib.inference.ObservationMetadata
NATIVE_CPU - Enum constant in enum class jdistlib.accelerator.ExecutionKind
nativeFactorizations() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether factorization methods execute natively on this provider.
nativeSparseFactorizations() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether sparse Cholesky analysis, factorization, and solves execute natively.
NATURAL - Enum constant in enum class jdistlib.accelerator.SparseOrdering: Preserve the input row and column order.
ncp - Variable in class jdistlib.NonCentralBeta
ncp - Variable in class jdistlib.NonCentralChiSquare
ncp - Variable in class jdistlib.NonCentralF
ncp - Variable in class jdistlib.NonCentralT
negate(int) - Method in class jdistlib.inference.autodiff.ReverseTape
NegativeHypergeometric - Class in jdistlib: Number of draws needed to observe r white balls without replacement.
NegativeHypergeometric(int, int, int) - Constructor for class jdistlib.NegativeHypergeometric
NegBinomial - Class in jdistlib
NegBinomial(double, double) - Constructor for class jdistlib.NegBinomial
nestedRankNormalizedRHat(double[][], int[]) - Static method in class jdistlib.inference.McmcDiagnostics: Rank-normalized and folded nested R-hat, matching the robust ordinary diagnostic.
nestedRankNormalizedRHat(int) - Method in class jdistlib.inference.ManyShortChainsResult
nestedRHat(double[][], int[]) - Static method in class jdistlib.inference.McmcDiagnostics: Nested R-hat for chains grouped by common-initialization superchain IDs.
nestedRHat(int) - Method in class jdistlib.inference.ManyShortChainsResult
neval - Variable in class jdistlib.math.IntegrationResult
next(int) - Method in class jdistlib.rng.MersenneTwisterSafe: Returns an integer with bits bits filled with a random number.
nextBlock(int, long[], int) - Method in class jdistlib.rng.RandomSampler: Computes the next count random numbers of the sorted random set specified on instance construction and fills them into values, starting at index fromIndex.
nextBoolean() - Method in class jdistlib.rng.MersenneTwister
nextBoolean() - Method in class jdistlib.rng.MersenneTwisterSafe: This method is missing from jdk 1.0.x and below.
nextBoolean(double) - Method in class jdistlib.rng.MersenneTwister: This generates a coin flip with a probability probability of returning true, else returning false.
nextBoolean(double) - Method in class jdistlib.rng.MersenneTwisterSafe: This generates a coin flip with a probability probability of returning true, else returning false.
nextBoolean(float) - Method in class jdistlib.rng.MersenneTwister: This generates a coin flip with a probability probability of returning true, else returning false.
nextBoolean(float) - Method in class jdistlib.rng.MersenneTwisterSafe: This generates a coin flip with a probability probability of returning true, else returning false.
nextByte() - Method in class jdistlib.rng.MersenneTwister
nextByte() - Method in class jdistlib.rng.MersenneTwisterSafe: For completeness' sake, though it's not in java.util.Random.
nextBytes(byte[]) - Method in class jdistlib.rng.MersenneTwister
nextBytes(byte[]) - Method in class jdistlib.rng.MersenneTwisterSafe: A bug fix for all versions of the JDK.
nextChar() - Method in class jdistlib.rng.MersenneTwister
nextChar() - Method in class jdistlib.rng.MersenneTwisterSafe: For completeness' sake, though it's not in java.util.Random.
nextDouble() - Method in class jdistlib.rng.MersenneTwister: Returns a random double in the half-open range from [0.0,1.0).
nextDouble() - Method in class jdistlib.rng.MersenneTwisterSafe: A bug fix for versions of JDK 1.1 and below.
nextDouble() - Method in class jdistlib.rng.RandomCMWC
nextDouble() - Method in class jdistlib.rng.RandomEngine
nextDouble() - Method in class jdistlib.rng.RandomWELL44497b
nextDouble(boolean, boolean) - Method in class jdistlib.rng.MersenneTwister: Returns a double in the range from 0.0 to 1.0, possibly inclusive of 0.0 and 1.0 themselves.
nextDouble(boolean, boolean) - Method in class jdistlib.rng.MersenneTwisterSafe: Returns a double in the range from 0.0 to 1.0, possibly inclusive of 0.0 and 1.0 themselves.
nextFloat() - Method in class jdistlib.rng.MersenneTwister: Returns a random float in the half-open range from [0.0f,1.0f).
nextFloat() - Method in class jdistlib.rng.MersenneTwisterSafe: A bug fix for versions of JDK 1.1 and below.
nextFloat() - Method in class jdistlib.rng.RandomCMWC
nextFloat() - Method in class jdistlib.rng.RandomEngine
nextFloat() - Method in class jdistlib.rng.RandomWELL44497b
nextFloat(boolean, boolean) - Method in class jdistlib.rng.MersenneTwister: Returns a float in the range from 0.0f to 1.0f, possibly inclusive of 0.0f and 1.0f themselves.
nextFloat(boolean, boolean) - Method in class jdistlib.rng.MersenneTwisterSafe: Returns a float in the range from 0.0f to 1.0f, possibly inclusive of 0.0f and 1.0f themselves.
nextGaussian() - Method in class jdistlib.rng.MersenneTwister
nextGaussian() - Method in class jdistlib.rng.MersenneTwisterSafe: A bug fix for all JDK code including 1.2.
nextGaussian() - Method in class jdistlib.rng.RandomCMWC
nextGaussian() - Method in class jdistlib.rng.RandomEngine
nextGaussian() - Method in class jdistlib.rng.RandomWELL44497b
nextInt() - Method in class jdistlib.rng.MersenneTwister
nextInt() - Method in class jdistlib.rng.MersenneTwisterSafe
nextInt() - Method in class jdistlib.rng.RandomCMWC
nextInt() - Method in class jdistlib.rng.RandomEngine
nextInt() - Method in class jdistlib.rng.RandomWELL44497b
nextInt(int) - Method in class jdistlib.rng.MersenneTwister: Returns an integer drawn uniformly from 0 to n-1.
nextInt(int) - Method in class jdistlib.rng.MersenneTwisterSafe: This method is missing from JDK 1.1 and below.
nextInt(int) - Method in class jdistlib.rng.RandomCMWC
nextInt(int) - Method in class jdistlib.rng.RandomEngine
nextInt(int) - Method in class jdistlib.rng.RandomWELL44497b
nextLong() - Method in class jdistlib.rng.MersenneTwister: Returns a long drawn uniformly from 0 to n-1.
nextLong() - Method in class jdistlib.rng.MersenneTwisterSafe: Returns a long drawn uniformly from 0 to n-1.
nextLong() - Method in class jdistlib.rng.RandomCMWC
nextLong() - Method in class jdistlib.rng.RandomEngine
nextLong() - Method in class jdistlib.rng.RandomWELL44497b
nextLong(long) - Method in class jdistlib.rng.MersenneTwister: Returns a long drawn uniformly from 0 to n-1.
nextLong(long) - Method in class jdistlib.rng.MersenneTwisterSafe: This method is for completness' sake.
nextLong(long) - Method in class jdistlib.rng.RandomCMWC
nextLong(long) - Method in class jdistlib.rng.RandomEngine
nextLong(long) - Method in class jdistlib.rng.RandomWELL44497b
nextShort() - Method in class jdistlib.rng.MersenneTwister
nextShort() - Method in class jdistlib.rng.MersenneTwisterSafe: For completeness' sake, though it's not in java.util.Random.
NO_CRITERION - Enum constant in enum class jdistlib.math.spline.SmoothSplineCriterion
nodes() - Method in class jdistlib.inference.ModelGraph
NON_FINITE_VALUE - Enum constant in enum class jdistlib.math.IntegrationStatus
NON_UNIT - Enum constant in enum class jdistlib.accelerator.MatrixDiagonal
NonCentralBeta - Class in jdistlib
NonCentralBeta(double, double, double) - Constructor for class jdistlib.NonCentralBeta
NonCentralChiSquare - Class in jdistlib
NonCentralChiSquare(double, double) - Constructor for class jdistlib.NonCentralChiSquare
NonCentralF - Class in jdistlib
NonCentralF(double, double, double) - Constructor for class jdistlib.NonCentralF
NonCentralT - Class in jdistlib
NonCentralT(double, double) - Constructor for class jdistlib.NonCentralT
NONE - Enum constant in enum class jdistlib.accelerator.MatrixTranspose: Use the stored matrix without transposition.
NONE - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: No adjustment.
NONFINITE_CONTRIBUTION - Enum constant in enum class jdistlib.CopulaLikelihoodDiagnostics.Status
nonFiniteResults() - Method in class jdistlib.inference.FactorProfile
nonlinearOptions - Variable in class jdistlib.inference.solver.StiffOdeSolver.Options
nonzeroCount() - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
nonzeroCount() - Method in interface jdistlib.accelerator.PreparedCsrMatrix
nonzeroCount() - Method in interface jdistlib.accelerator.PreparedFloatCsrMatrix
nonzeroCount() - Method in class jdistlib.accelerator.SparseCholeskyFactor
nonzeroCount() - Method in class jdistlib.matrix.CsrMatrix
nonzeroCount() - Method in class jdistlib.matrix.FloatCsrMatrix
norm() - Method in class jdistlib.math.Complex
Normal - Class in jdistlib: Manually translated from R's Distlib by Roby Joehanes
Normal() - Constructor for class jdistlib.Normal: Constructor for standard normal (i.e., mean = 0, sd = 1)
Normal(double, double) - Constructor for class jdistlib.Normal
normalInverseGaussian(double, double, double[], double[], double[][]) - Static method in class jdistlib.finance.MultivariateFinancialDistribution
normalInverseGaussian(double, double, double, double) - Static method in class jdistlib.finance.GeneralizedHyperbolicDistribution
NormalInverseGaussianDistribution - Class in jdistlib.finance: Named NIG specialization of the generalized-hyperbolic family.
NormalInverseGaussianDistribution(double, double, double, double) - Constructor for class jdistlib.finance.NormalInverseGaussianDistribution
NormalityTest - Class in jdistlib.disttest: A package about normality testing.
NormalityTest() - Constructor for class jdistlib.disttest.NormalityTest
normalObservations(String, String, double) - Static method in class jdistlib.inference.ModelFactors
normalPrior(String, double, double) - Static method in class jdistlib.inference.ModelFactors
normalTemperedStable(double, double, double, double[], double[], double[][]) - Static method in class jdistlib.finance.MultivariateFinancialDistribution: Multivariate normal-tempered-stable normal variance mixture.
NormalTemperedStableDistribution - Class in jdistlib.finance: Normal-tempered-stable law defined by a tempered-stable normal variance mixture.
NormalTemperedStableDistribution(double, double, double, double, double, double) - Constructor for class jdistlib.finance.NormalTemperedStableDistribution
NormalTemperedStableDistribution(double, double, double, double, double, double, FourierInversionOptions) - Constructor for class jdistlib.finance.NormalTemperedStableDistribution
NOT_BRACKETED - Enum constant in enum class jdistlib.finance.ImpliedVolatilityResult.Status
NoUTurnSampler - Class in jdistlib.inference: Multinomial-candidate NUTS with windowed adaptation and configurable metrics.
NoUTurnSampler() - Constructor for class jdistlib.inference.NoUTurnSampler
npq - Variable in class jdistlib.Binomial.RandomState
NRD - Static variable in class jdistlib.math.density.Bandwidth
NRD(double[]) - Static method in class jdistlib.math.density.Bandwidth
NRD0 - Static variable in class jdistlib.math.density.Bandwidth
NRD0(double[]) - Static method in class jdistlib.math.density.Bandwidth
NRM2 - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
nsave - Variable in class jdistlib.Binomial.RandomState
NUMERICAL_FAILURE - Enum constant in enum class jdistlib.CopulaFitResult.Status
NUMERICAL_FAILURE - Enum constant in enum class jdistlib.inference.ChainResult.Status
NUMERICAL_FAILURE - Enum constant in enum class jdistlib.inference.ReversibleJumpResult.Status
NUMERICAL_FAILURE - Enum constant in enum class jdistlib.inference.SparseSubsetResult.Status
NUMERICAL_FAILURE - Enum constant in enum class jdistlib.VineFitResult.Status
NUMERICAL_MIXED_DERIVATIVE - Enum constant in enum class jdistlib.CopulaMeasureResult.Status
NUMERICAL_WARNING - Enum constant in enum class jdistlib.CopulaLogLikelihoodResult.Status
NUMERICAL_WARNING - Enum constant in enum class jdistlib.CopulaMeasureResult.Status
NumericalCdfTable - Class in jdistlib: Reusable monotone CDF approximation built from directly integrated values.
NumericalContinuousDistribution - Class in jdistlib: A continuous distribution obtained by numerically normalizing a nonnegative kernel over a real interval.
NumericalContinuousDistribution(UnivariateFunction, double, double) - Constructor for class jdistlib.NumericalContinuousDistribution: Constructs a distribution using distribution-oriented integration defaults: relative tolerance 1e-10, 300 subdivisions, a finite evaluation budget, and automatic finite-interval tanh-sinh fallback.
NumericalContinuousDistribution(UnivariateFunction, double, double, double, double, int) - Constructor for class jdistlib.NumericalContinuousDistribution: Constructs a distribution with explicit QUADPACK tolerances.
NumericalContinuousDistribution(UnivariateFunction, double, double, IntegrationOptions) - Constructor for class jdistlib.NumericalContinuousDistribution: Constructs a distribution with hardened integration options.
NumericalContinuousDistribution.Builder - Class in jdistlib: Fluent construction with optional analysis and sampling configuration.
NumericalDiscreteDistribution - Class in jdistlib: A finite discrete distribution obtained by normalizing a nonnegative weight function over a declared set of numeric outcomes.
NumericalDiscreteDistribution(UnivariateFunction, double[]) - Constructor for class jdistlib.NumericalDiscreteDistribution: Constructs a distribution over an arbitrary finite set of outcomes.
NumericalDiscreteDistribution(UnivariateFunction, int, int) - Constructor for class jdistlib.NumericalDiscreteDistribution: Constructs a distribution over every integer in the inclusive range.
NumericalDiscreteDistribution.Builder - Class in jdistlib
NumericalDistributionAnalyzer - Class in jdistlib: Self-consistency and moment diagnostics for numerical distributions.
NumericalDistributionBuildResult - Class in jdistlib: Analysis plus the result of attempting to construct a numerical distribution.
NumericalEstimate - Class in jdistlib.finance: Immutable diagnostics for an approximate scalar calculation.
NumericalEstimate(double, double, boolean, int, String, String) - Constructor for class jdistlib.finance.NumericalEstimate
numericalFailures() - Method in class jdistlib.inference.SamplerDiagnostics
NumericalPiecewiseDistribution - Class in jdistlib: Numerical distribution over a union of continuous intervals and optional point atoms.
NumericalPiecewiseDistribution(UnivariateFunction, NumericalSupport, IntegrationOptions) - Constructor for class jdistlib.NumericalPiecewiseDistribution
NumericalPiecewiseDistribution(UnivariateFunction, NumericalSupport, UnivariateFunction, IntegrationOptions) - Constructor for class jdistlib.NumericalPiecewiseDistribution
NumericalPiecewiseDistribution.Builder - Class in jdistlib
NumericalSupport - Class in jdistlib: Immutable union of continuous intervals, optional atoms, and singularities.
NumericalSupport.Builder - Class in jdistlib: Builder supporting interval unions followed by hole subtraction.
NumericalSupport.Interval - Class in jdistlib: One nonempty continuous interval.
NumericPrecision - Enum Class in jdistlib.accelerator: Storage and arithmetic precision requested for a linear-algebra operation.
numFunctionCalls - Variable in class jdistlib.math.opt.OptimizationResult
numInterpolationPoints - Variable in class jdistlib.math.opt.BobyqaConfig
nutsBackend() - Method in class jdistlib.inference.InferenceCliOptions
nutsBackend() - Method in class jdistlib.inference.SamplingOptions: NUTS-specific accelerator policy; tree construction always remains on CPU.
nutsBackend(ComputeNuts) - Method in class jdistlib.inference.SamplingOptions.Builder: Selects off, automatic, or forced NUTS target offload.
nutsOffload() - Method in class jdistlib.inference.RunManifest

O

objective() - Method in class jdistlib.inference.OptimizationResult
objective() - Method in class jdistlib.inference.PredictiveStacking.Result
objectiveFunction - Variable in class jdistlib.math.opt.OptimizationConfig
objectives() - Method in class jdistlib.inference.OptimizationTrace
observationCount() - Method in class jdistlib.inference.PsisLoo.Result
observationMetadata() - Method in class jdistlib.inference.BayesianModel
observationMetadata() - Method in interface jdistlib.inference.PointwiseLogLikelihood
ObservationMetadata - Class in jdistlib.inference: Immutable names and grouping labels for pointwise likelihood contributions.
ObservationMetadata(String[], String[]) - Constructor for class jdistlib.inference.ObservationMetadata
observations() - Method in class jdistlib.finance.EmpiricalDistribution
observations() - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
OdeSolver - Class in jdistlib.inference.solver: Adaptive Dormand-Prince 5(4) ODE integration at requested output times.
OdeSolver.Options - Class in jdistlib.inference.solver: Integration controls.
OdeSystem - Interface in jdistlib.inference.solver: First-order ordinary differential equation y' = f(t,y).
OFF - Enum constant in enum class jdistlib.inference.ComputeNuts: Require CPU target evaluation for NUTS.
offsetMultiplier(double, double, int) - Static method in class jdistlib.inference.Constraints
omega - Variable in class jdistlib.Nakagami
omittedProbabilityTolerance(double) - Method in class jdistlib.CertifiedDiscreteOptions.Builder
ONE - Static variable in class jdistlib.math.Complex
ONEMKL - Enum constant in enum class jdistlib.accelerator.Compute: Require the optional Intel oneMKL native CPU provider.
ONEMKL - Enum constant in enum class jdistlib.accelerator.ComputeApi
OnlineFdr - Class in jdistlib.disttest.online: Utilities shared by online false-discovery-rate controllers.
OnlineFdrController - Interface in jdistlib.disttest.online: A stateful controller for hypotheses arriving in a fixed sequential order.
OnlineFdrDecision - Class in jdistlib.disttest.online: Immutable record of one online-FDR test.
OPENBLAS - Enum constant in enum class jdistlib.accelerator.Compute: Require the optional OpenBLAS native CPU provider.
OPENBLAS - Enum constant in enum class jdistlib.accelerator.ComputeApi
OPENCL - Enum constant in enum class jdistlib.accelerator.Compute: Require the optional OpenCL provider.
OPENCL - Enum constant in enum class jdistlib.accelerator.ComputeApi
operation() - Method in class jdistlib.accelerator.ExecutionPlan
OPTCOSINE - Enum constant in enum class jdistlib.math.density.Kernel
optimization() - Method in class jdistlib.inference.PathfinderResult
Optimization - Class in jdistlib.math.opt: Function optimization routines.
Optimization() - Constructor for class jdistlib.math.opt.Optimization
OptimizationConfig - Class in jdistlib.math.opt
OptimizationConfig() - Constructor for class jdistlib.math.opt.OptimizationConfig
OptimizationConfig(double[], double[], double[], MultivariableFunction) - Constructor for class jdistlib.math.opt.OptimizationConfig
OptimizationConfig(double[], double[], double[], MultivariableFunction, int, boolean) - Constructor for class jdistlib.math.opt.OptimizationConfig
OptimizationResult - Class in jdistlib.inference: Immutable numerical-optimization result.
OptimizationResult - Class in jdistlib.math.opt: Class to hold optimization results
OptimizationResult() - Constructor for class jdistlib.math.opt.OptimizationResult
OptimizationResult(double[], double, int, boolean) - Constructor for class jdistlib.math.opt.OptimizationResult
optimizations() - Method in class jdistlib.inference.PathfinderFit
OptimizationTrace - Class in jdistlib.inference: Accepted L-BFGS path used by Pathfinder approximation selection.
optimize(OptimizationConfig) - Method in class jdistlib.math.opt.Bobyqa
optimize(OptimizationConfig) - Method in class jdistlib.math.opt.MultivariateOptimization
optimize(UnivariateFunction, double, double) - Static method in class jdistlib.math.opt.Optimization: Brent's minimization function with default tolerance (1e-10)
optimize(UnivariateFunction, double, double, double, int) - Static method in class jdistlib.math.opt.Optimization: Richard Brent's function minimization routine.
Wikipedia's link
Adapted from Netlib's fmin.
Also looked at Numerical Methods in C, 2nd ed.
OptionCalibration - Class in jdistlib.finance: Fits caller-supplied parametric terminal laws directly to European option quotes.
OptionCalibration.Family - Interface in jdistlib.finance
OptionCalibration.Result - Class in jdistlib.finance
OptionCurve - Class in jdistlib.finance: Arbitrage-repaired European option curve and its implied risk-neutral law.
OptionCurve.Diagnostics - Class in jdistlib.finance
OptionImpliedDistribution - Class in jdistlib.finance: Atom-aware risk-neutral law recovered from a convex piecewise-linear call curve.
OptionInference - Class in jdistlib.finance: Option-price likelihood factors and posterior-predictive distribution adapters.
OptionInference.DrawDistribution - Interface in jdistlib.finance
OptionInference.Measure - Enum Class in jdistlib.finance
OptionInference.PosteriorEnsemble - Class in jdistlib.finance
OptionInference.StateNoiseModel - Interface in jdistlib.finance
OptionInference.StatePriceModel - Interface in jdistlib.finance
OptionObservation - Class in jdistlib.finance: Immutable European option quote used by the narrow option-implied layer.
OptionObservation(double, boolean, double) - Constructor for class jdistlib.finance.OptionObservation
OptionObservation(double, boolean, double, double, double) - Constructor for class jdistlib.finance.OptionObservation
options() - Method in enum class jdistlib.DiagnosticPreset: Creates independently editable settings for this preset.
Options(double, double, double, int) - Constructor for class jdistlib.inference.solver.OdeSolver.Options
Options(double, double, double, int, AlgebraicSolver.Options) - Constructor for class jdistlib.inference.solver.StiffOdeSolver.Options
Options(double, double, int) - Constructor for class jdistlib.inference.solver.AlgebraicSolver.Options
optionsFingerprint() - Method in class jdistlib.inference.PortableCheckpoint
optionsFingerprint() - Method in class jdistlib.inference.PortableReversibleJumpCheckpoint
optionsFingerprint() - Method in class jdistlib.inference.PortableSparseSubsetCheckpoint
optionsHash() - Method in class jdistlib.inference.RunManifest
order(double[]) - Static method in class jdistlib.util.Utilities: Returns the order of the elements of array e
Order - Class in jdistlib.evd: Order distribution.
Order(GenericDistribution, int, int, boolean) - Constructor for class jdistlib.evd.Order
ordered(int) - Static method in class jdistlib.inference.Constraints
orders(double...) - Method in class jdistlib.MomentAnalysisOptions.Builder
OrderStatisticDistribution - Class in jdistlib.finance: Exact minimum or maximum of independent identically distributed variables.

P

p - Variable in class jdistlib.Binomial
p - Variable in class jdistlib.Geometric
p1 - Variable in class jdistlib.Binomial.RandomState
p1 - Variable in class jdistlib.HyperGeometric.RandomState
p2 - Variable in class jdistlib.Binomial.RandomState
p2 - Variable in class jdistlib.HyperGeometric.RandomState
p3 - Variable in class jdistlib.Binomial.RandomState
p3 - Variable in class jdistlib.HyperGeometric.RandomState
p4 - Variable in class jdistlib.Binomial.RandomState
packed() - Method in class jdistlib.accelerator.FloatLuFactor
packed() - Method in class jdistlib.accelerator.FloatPivotedQrFactor
packed() - Method in class jdistlib.accelerator.LuFactor: Returns packed unit-lower and upper factors in row-major storage.
packed() - Method in class jdistlib.accelerator.PivotedQrFactor: Returns a row-major copy containing R and the packed Householder vectors.
PAIR_FIT_FAILED - Enum constant in enum class jdistlib.VineFitResult.Status
PairCopula - Class in jdistlib: Bivariate copula adapter exposing conditional CDFs and their inverses.
PairCopula(Copula) - Constructor for class jdistlib.PairCopula
PairCopula(Copula, double) - Constructor for class jdistlib.PairCopula
pairs(String, int, String, int, ChainResult...) - Static method in class jdistlib.inference.DiagnosticGraphs
panjerCompound(double, double, double, double[], int) - Static method in class jdistlib.finance.DistributionAggregation: Panjer (a,b,0) recursion; countAtZero is P(N=0), including severity mass at zero.
parallel(ReversibleJumpSamplerFactory, ReversibleJumpTarget, ReversibleJumpState[], ReversibleJumpSamplingOptions, long, int) - Static method in class jdistlib.inference.ReversibleJumpChains
parallel(Sampler, LogDensity, double[][], SamplingOptions, long, int) - Static method in class jdistlib.inference.Chains
ParallelTempering - Class in jdistlib.inference: Replica exchange using random-walk within-temperature transitions.
ParallelTemperingResult - Class in jdistlib.inference: Cold-chain draws and adjacent-temperature swap diagnostics.
parameter(int) - Method in class jdistlib.inference.ReversibleJumpState
parameter(String) - Method in class jdistlib.inference.McmcDiagnosticReport
parameter(String, ParameterConstraint, double...) - Method in class jdistlib.inference.ModelBuilder
PARAMETER - Enum constant in enum class jdistlib.inference.ModelGraph.NodeKind
ParameterConstraint - Interface in jdistlib.inference: A differentiable map from unconstrained coordinates to constrained values.
parameterCount() - Method in interface jdistlib.finance.DistributionFit.ParametricFamily
ParameterDiagnostics - Class in jdistlib.inference: Posterior summary and modern multi-chain convergence diagnostics.
parameterDimension(String) - Method in class jdistlib.inference.ModelState
parameterFromKendallsTau(double) - Static method in class jdistlib.ClaytonCopula
parameterFromKendallsTau(double) - Static method in class jdistlib.FrankCopula: Numerically inverts the Frank tau relationship.
parameterFromKendallsTau(double) - Static method in class jdistlib.GumbelCopula
parameterIndex(long, int) - Method in class jdistlib.inference.SubsetSelectionTarget
parameterName(int) - Method in class jdistlib.inference.ReversibleJumpModelSpace
parameterNames() - Method in class jdistlib.inference.ReversibleJumpModelSpace
parameters() - Method in class jdistlib.inference.BayesianModel
parameters() - Method in class jdistlib.inference.McmcDiagnosticReport
parameters() - Method in class jdistlib.inference.ReversibleJumpState
ParameterSpec - Class in jdistlib.inference: Immutable parameter metadata in a compiled Bayesian model.
parameterSummaries() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
paretoK() - Method in class jdistlib.inference.ParetoSmoothedImportanceSampling.Result
paretoK() - Method in class jdistlib.inference.PathfinderFit
paretoK() - Method in class jdistlib.inference.PsisLoo.Result
ParetoSmoothedImportanceSampling - Class in jdistlib.inference: Pareto-tail smoothing for log importance ratios, with a diagnostic shape estimate.
ParetoSmoothedImportanceSampling.Result - Class in jdistlib.inference
parse(String) - Static method in enum class jdistlib.accelerator.Compute: Parses a case-insensitive command-line or system-property value.
parse(String) - Static method in enum class jdistlib.inference.ComputeNuts: Parses a case-insensitive command-line or system-property value.
parse(String[]) - Static method in class jdistlib.inference.InferenceCliOptions: Recognizes --compute, --nuts-offload, and --gpu-nuts; unrecognized arguments are retained for the host application.
partialMoment(GenericDistribution, double, double, Tail) - Static method in class jdistlib.finance.FinancialRisk: Lower/upper partial moment E[(threshold-X)+^order] or E[(X-threshold)+^order].
passed() - Method in class jdistlib.inference.GradientCheckResult
path() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Result
Pathfinder - Class in jdistlib.inference: Multi-path quasi-Newton Gaussian approximation with mixture scoring and PSIS resampling.
PathfinderFit - Class in jdistlib.inference: Multi-path Gaussian approximation, PSIS diagnostic, and resampled draws.
PathfinderInitializer - Class in jdistlib.inference: L-BFGS path plus local Gaussian draw for robust chain initialization.
PathfinderOptions - Class in jdistlib.inference: Immutable controls for multi-path Pathfinder initialization and sampling.
PathfinderOptions.Builder - Class in jdistlib.inference
PathfinderResult - Class in jdistlib.inference: Quasi-Newton Gaussian initialization result.
PathFunctionalDistributions - Class in jdistlib.finance: Exact iid-observation extrema and simulated drawdowns for iid discrete-time increments.
paths() - Method in class jdistlib.inference.PathfinderOptions
paths(int) - Method in class jdistlib.inference.PathfinderOptions.Builder
payoffDistribution(double, boolean) - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
pd_lower_cf(double, double) - Static method in class jdistlib.math.MathFunctions
pd_lower_series(double, double) - Static method in class jdistlib.math.MathFunctions
pd_upper_series(double, double, boolean) - Static method in class jdistlib.math.MathFunctions
pdhyper(double, double, double, double, boolean) - Static method in class jdistlib.HyperGeometric
pentagamma(double) - Static method in class jdistlib.math.PolyGamma
pentagamma(double[]) - Static method in class jdistlib.math.PolyGamma
Performance (200Mhz Pentium Pro, JDK 1.2, NT) - Search tag in class jdistlib.rng.RandomSampler: Section
PERMISSIVE - Enum constant in enum class jdistlib.ConstructionPolicy: Analysis never prevents an attempt, though hard numerical failures still do.
permutation() - Method in class jdistlib.accelerator.FloatLuFactor
permutation() - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
permutation() - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
permutation() - Method in class jdistlib.accelerator.LuFactor: Returns the new-to-original row permutation.
permutation() - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
permutation() - Method in interface jdistlib.accelerator.PreparedSparseCholesky: Returns the new-to-original permutation, or an empty array when provider-owned.
permutation() - Method in class jdistlib.accelerator.SparseCholeskyFactor: Returns the new-to-original symmetric permutation used by the factor.
permutation() - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
permute(double[]) - Static method in class jdistlib.util.Utilities: Permute the array e
permute(double[], RandomEngine) - Static method in class jdistlib.util.Utilities: Permute the array e
phase(int) - Method in class jdistlib.inference.WarmupSchedule.Resolved
PhaseType - Class in jdistlib: Continuous phase-type law with an optional atom at zero.
PhaseType(double[], double[][]) - Constructor for class jdistlib.PhaseType
phi - Variable in class jdistlib.Tweedie
PHYSICAL_PREDICTIVE - Enum constant in enum class jdistlib.finance.OptionInference.Measure
pickands(double[], int) - Static method in class jdistlib.finance.ExtremeValueInference
pilotDraws() - Method in class jdistlib.inference.AdjustedMclmcTuningOptions
pilotDraws(int) - Method in class jdistlib.inference.AdjustedMclmcTuningOptions.Builder
pilotWarmup() - Method in class jdistlib.inference.AdjustedMclmcTuningOptions
pilotWarmup(int) - Method in class jdistlib.inference.AdjustedMclmcTuningOptions.Builder
pivot() - Method in class jdistlib.accelerator.FloatPivotedQrFactor
pivot() - Method in class jdistlib.accelerator.PivotedQrFactor: Returns the permutation where factor column j came from original column pivot[j].
PivotedQrFactor - Class in jdistlib.accelerator: Immutable column-pivoted Householder QR factorization.
PivotedQrFactor(int, int, double[], double[], int[]) - Constructor for class jdistlib.accelerator.PivotedQrFactor: Creates a factor from packed Householder QR storage and a zero-based pivot.
plan() - Method in class jdistlib.inference.ManyShortChainsResult
plan(LinearAlgebraOperation, NumericPrecision, int...) - Method in interface jdistlib.accelerator.ComputeBackend: Predicts execution for the supplied operation and dimensions without running it.
plan(LinearAlgebraOperation, NumericPrecision, int...) - Method in class jdistlib.accelerator.ComputeSelection: Predicts the concrete execution route for an operation without running it.
platform() - Method in class jdistlib.inference.PortableCheckpoint
platform() - Method in class jdistlib.inference.PortableReversibleJumpCheckpoint
platform() - Method in class jdistlib.inference.PortableSparseSubsetCheckpoint
plus(LevyIncrementDistribution) - Method in class jdistlib.finance.LevyIncrementDistribution: Exact composition of independent increments sharing this unit exponent.
plus(Polynomial) - Method in class jdistlib.math.Polynomial: Add another polynomial to this polynomial and store the result into a new instance of QPolynomial
plusEquals(Polynomial) - Method in class jdistlib.math.Polynomial: Add another polynomial into this polynomial and let the result overwrite this polynomial (this = this + poly)
pmax(double[], double[]) - Static method in class jdistlib.math.VectorMath
pmin(double[], double[]) - Static method in class jdistlib.math.VectorMath
point() - Method in class jdistlib.inference.OptimizationResult
points() - Method in class jdistlib.inference.OptimizationTrace
pointwiseElpd() - Method in class jdistlib.inference.PsisLoo.Result
pointwiseElpd() - Method in class jdistlib.inference.Waic.Result
pointwiseLikelihood(ObservationMetadata, PointwiseLogLikelihoodEvaluator) - Method in class jdistlib.inference.ModelBuilder: Registers likelihood contributions already included in the model target.
pointwiseLogLikelihood(double[]) - Method in class jdistlib.inference.BayesianModel
pointwiseLogLikelihood(double[]) - Method in interface jdistlib.inference.PointwiseLogLikelihood
PointwiseLogLikelihood - Interface in jdistlib.inference: Model contract required by pointwise predictive assessment.
PointwiseLogLikelihoodDraws - Class in jdistlib.inference: Pointwise log likelihoods with retained chain boundaries and observation metadata.
PointwiseLogLikelihoodDraws(ObservationMetadata, double[][], int[]) - Constructor for class jdistlib.inference.PointwiseLogLikelihoodDraws
PointwiseLogLikelihoodEvaluator - Interface in jdistlib.inference: Evaluates ordered observation-level log-likelihood contributions.
Poisson - Class in jdistlib
Poisson(double) - Constructor for class jdistlib.Poisson
poisson_test(int, double, double, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Performs an exact test of a simple null hypothesis about the rate parameter in Poisson distribution
poisson_test(int, int, double, double, double, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Comparison of Poisson rates
Poisson.RandomState - Class in jdistlib
PoissonBinomial - Class in jdistlib: Sum of independent Bernoulli trials with unequal success probabilities.
PoissonBinomial(double[]) - Constructor for class jdistlib.PoissonBinomial
PoissonInverseGaussian - Class in jdistlib: Poisson-inverse Gaussian distribution from actuar.
PoissonInverseGaussian(double, double) - Constructor for class jdistlib.PoissonInverseGaussian
PolyaAeppliDistribution - Class in jdistlib.finance: Polya-Aeppli count: Poisson clusters with shifted-geometric cluster sizes.
PolyaAeppliDistribution(double, double) - Constructor for class jdistlib.finance.PolyaAeppliDistribution
PolyGamma - Class in jdistlib.math: Mathlib : A C Library of Special Functions Copyright (C) 1998 Ross Ihaka Copyright (C) 2000-2007 the R Development Core Team Copyright (C) 2004 The R Foundation This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
PolyGamma() - Constructor for class jdistlib.math.PolyGamma
Polynomial - Class in jdistlib.math: A Java object that represents polynomials as arrays of numerical coefficients.
Polynomial(double...) - Constructor for class jdistlib.math.Polynomial
Polynomial(int) - Constructor for class jdistlib.math.Polynomial
polynomialGamma(int, double) - Static method in class jdistlib.disttest.online.OnlineFdr: Returns a finite, normalized, nonincreasing gamma sequence proportional to index^-exponent; it is padded with zeros beyond the horizon.
PORTABLE_FALLBACK - Enum constant in enum class jdistlib.accelerator.ExecutionKind
PortableCheckpoint - Class in jdistlib.inference: Checkpoint plus the fingerprints and platform metadata needed to validate a resume.
PortableReversibleJumpCheckpoint - Class in jdistlib.inference: Restored RJ checkpoint plus the fingerprints and platform recorded with it.
PortableSparseSubsetCheckpoint - Class in jdistlib.inference: Restored sparse checkpoint plus its model/options fingerprints and platform.
position() - Method in class jdistlib.inference.KernelTransition
position() - Method in class jdistlib.inference.RandomWalkKernel.State
positions() - Method in class jdistlib.inference.solver.HigherIndexDaeSolver.Result
positive() - Static method in class jdistlib.inference.Constraints
PositiveNormal - Class in jdistlib: Normal distribution left-truncated at zero.
PositiveNormal(double, double) - Constructor for class jdistlib.PositiveNormal
positiveOrdered(int) - Static method in class jdistlib.inference.Constraints
PositiveTemperedStableDistribution - Class in jdistlib.finance: Positive tempered-stable subordinator increment with Laplace exponent.
PositiveTemperedStableDistribution(double, double, double) - Constructor for class jdistlib.finance.PositiveTemperedStableDistribution
positiveVector(int) - Static method in class jdistlib.inference.Constraints
posterior(double[][], OptionInference.DrawDistribution, OptionInference.Measure, long, String) - Static method in class jdistlib.finance.OptionInference
posteriorMean() - Method in class jdistlib.inference.ShrinkageSelection.Variable
posteriorMeanAbsoluteMagnitude() - Method in class jdistlib.inference.ShrinkageSelection.Variable
POTRF - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
pow(int, double) - Method in class jdistlib.inference.autodiff.ReverseTape
pow(int, int) - Method in class jdistlib.inference.autodiff.ReverseTape
pow(Complex) - Method in class jdistlib.math.Complex
pow1p(double, double) - Static method in class jdistlib.math.MathFunctions: Computes (1 + x)^y without discarding a small x.
practicalMagnitude() - Method in class jdistlib.inference.ShrinkageSelection.Result
precision() - Method in class jdistlib.accelerator.ExecutionPlan
PrecisionContinuation - Class in jdistlib.inference: Chunked deterministic continuation based on MCSE, never on R-hat alone.
PrecisionContinuationResult - Class in jdistlib.inference: Deterministically extended chain and the reason continuation stopped.
PrecisionException - Exception Class in jdistlib.exception
PrecisionException(double) - Constructor for exception class jdistlib.exception.PrecisionException
PrecisionException(String, double) - Constructor for exception class jdistlib.exception.PrecisionException
PrecisionException(String, Throwable, double) - Constructor for exception class jdistlib.exception.PrecisionException
PrecisionException(Throwable, double) - Constructor for exception class jdistlib.exception.PrecisionException
PrecisionGoal - Class in jdistlib.inference: Stopping goal for one posterior coordinate, guarded by minimum draws and chunk count.
PrecisionGoal.Builder - Class in jdistlib.inference
predict(double[], double[], double, double, double, int) - Static method in class jdistlib.math.spline.SmoothSpline
predict(SmoothSplineResult, double, int) - Static method in class jdistlib.math.spline.SmoothSpline
PredictiveStacking - Class in jdistlib.inference: Optimizes simplex weights for stacking pointwise out-of-sample predictions.
PredictiveStacking.Result - Class in jdistlib.inference
preferred() - Static method in class jdistlib.accelerator.ComputeBackends
PREPARED_CHOLESKY - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
PREPARED_CSR - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
PREPARED_DENSE - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
PreparedCholesky - Interface in jdistlib.accelerator: Reusable FP64 Cholesky factor that can solve multiple right sides in place.
prepareDcsr(CsrMatrix) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
PreparedCsrMatrix - Interface in jdistlib.accelerator: Reusable FP64 CSR handle; capabilities report whether storage is provider-resident.
prepareDcsrpotrf(CsrMatrix, MatrixTriangle) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
prepareDcsrpotrf(CsrMatrix, MatrixTriangle, SparseOrdering) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
preparedDenseMatrices() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether prepared dense handles retain provider-optimal storage between calls.
PreparedDenseMatrix - Interface in jdistlib.accelerator: Reusable FP64 dense matrix handle; providers may retain storage on device.
PreparedFloatCholesky - Interface in jdistlib.accelerator: Reusable FP32 Cholesky factor that can solve multiple right sides in place.
PreparedFloatCsrMatrix - Interface in jdistlib.accelerator: Reusable FP32 CSR handle; capabilities report whether storage is provider-resident.
PreparedFloatDenseMatrix - Interface in jdistlib.accelerator: Reusable FP32 dense matrix handle; providers may retain storage on device.
PreparedFloatSparseCholesky - Interface in jdistlib.accelerator: Symbolically analyzed FP32 sparse Cholesky handle with reusable numeric factors.
prepareDge(double[], int, int) - Method in interface jdistlib.accelerator.LinearAlgebraBackend
PreparedLogisticRegression - Interface in jdistlib.accelerator: A logistic-regression data set prepared for repeated batched evaluation.
prepareDpotrf(double[], int) - Method in interface jdistlib.accelerator.ComputeBackend: Prepares a reusable FP64 Cholesky factor and solve handle.
PreparedSparseCholesky - Interface in jdistlib.accelerator: Symbolically analyzed FP64 sparse Cholesky handle with reusable numeric factors.
preparedSparseMatrices() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether prepared CSR handles retain provider-optimal storage between calls.
PreparedTransposeProduct - Interface in jdistlib.accelerator: A row-by-feature matrix retained for repeated X'v score batches.
prepareLogisticRegression(double[][], double[]) - Method in interface jdistlib.accelerator.ComputeBackend: Keeps reusable data in backend-optimal storage when the backend supports it.
prepareLogisticRegression(double[][], double[]) - Method in class jdistlib.accelerator.CpuComputeBackend
prepareScsr(FloatCsrMatrix) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
prepareScsrpotrf(FloatCsrMatrix, MatrixTriangle) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
prepareScsrpotrf(FloatCsrMatrix, MatrixTriangle, SparseOrdering) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
prepareSge(float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
prepareSpotrf(float[], int) - Method in interface jdistlib.accelerator.ComputeBackend: Prepares a reusable FP32 Cholesky factor and solve handle.
prepareTransposeProduct(double[][]) - Method in interface jdistlib.accelerator.ComputeBackend: Keeps a reusable row-by-feature matrix ready for repeated X'v batches.
prepareTransposeProduct(double[][]) - Method in class jdistlib.accelerator.CpuComputeBackend
price(ModelState, OptionObservation) - Method in interface jdistlib.finance.OptionInference.StatePriceModel
PRICE_ABOVE_BOUND - Enum constant in enum class jdistlib.finance.ImpliedVolatilityResult.Status
PRICE_BELOW_BOUND - Enum constant in enum class jdistlib.finance.ImpliedVolatilityResult.Status
principalDirection() - Method in class jdistlib.inference.AdaptiveStaticHmcResult
print(double...) - Static method in class jdistlib.util.Utilities
print(String, double...) - Static method in class jdistlib.util.Utilities
prior(String, GenericDistribution) - Method in class jdistlib.inference.ModelBuilder: Adds an independent fixed scalar prior for a scalar parameter.
prob - Variable in class jdistlib.NegBinomial
probability - Variable in class jdistlib.MultivariateProbabilityResult: The requested probability.
probability - Variable in class jdistlib.VineProbabilityResult
probability(double[], double[], double[]) - Static method in class jdistlib.Dirichlet
probability(double[], double[], double[], double[][]) - Static method in class jdistlib.MultivariateCauchy
probability(double[], double[], double[], double[][]) - Static method in class jdistlib.MultivariateLaplace
probability(double[], double[], double[], double[][]) - Static method in class jdistlib.MultivariateLogNormal
probability(double[], double[], double[], double[][]) - Static method in class jdistlib.MultivariateNormal: Deterministic convenience overload using call-local randomized shifts.
probability(double[], double[], double[], double[][], double) - Static method in class jdistlib.MultivariatePowerExponential
probability(double[], double[], double[], double[][], double) - Static method in class jdistlib.MultivariateStudentT
probability(double[], double[], double[], double[][], double, MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariatePowerExponential: Computes a rectangle probability by integrating the exact conditional radial probability over uniformly distributed directions.
probability(double[], double[], double[], double[][], double, MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateStudentT: Computes P[lower <= X <= upper] with numerical error metadata.
probability(double[], double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateCauchy
probability(double[], double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateLaplace: Computes P(lower <= X <= upper) through the normal-exponential mixture.
probability(double[], double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateLogNormal: Computes a rectangular probability after the component-wise log transform.
probability(double[], double[], double[], double[][], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.MultivariateNormal: Computes P[lower <= X <= upper] with numerical error metadata.
probability(double[], double[], double[], MultivariateProbabilityOptions, RandomEngine) - Static method in class jdistlib.Dirichlet: Computes a simplex-aware rectangle probability.
probability(int[], int[], int[], int) - Static method in class jdistlib.MultivariateHypergeometric: Exact inclusive rectangle probability for the sampled category counts.
probability(int[], int[], int, double[]) - Static method in class jdistlib.DirichletMultinomial: Exact inclusive rectangle probability for the category counts.
probability(int[], int[], int, double[]) - Static method in class jdistlib.Multinomial: Exact inclusive rectangle probability for the category counts.
probabilityBeyondPracticalMagnitude() - Method in class jdistlib.inference.ShrinkageSelection.Variable
ProbabilityFunctionAnalyzer - Class in jdistlib: Advisory probes for user-supplied probability kernels.
probabilityInterval(double) - Method in class jdistlib.NumericalContinuousDistribution: Returns the equal-tail interval containing the requested probability.
probabilityInterval(double) - Method in class jdistlib.NumericalDiscreteDistribution: Returns an equal-tail interval; its actual discrete mass may exceed the request.
ProbabilityInterval - Class in jdistlib: Immutable interval containing a requested probability under a stated rule.
ProbabilityInterval(double, double, double, String) - Constructor for class jdistlib.ProbabilityInterval
PROBABLY_DIVERGENT - Enum constant in enum class jdistlib.math.IntegrationStatus
process(double, double[]) - Method in enum class jdistlib.math.density.Kernel
prod(double[]) - Static method in class jdistlib.math.VectorMath: Product of numbers.
product(GenericDistribution, GenericDistribution, int, long) - Static method in class jdistlib.finance.DistributionAggregation
profile() - Method in interface jdistlib.inference.ProfiledModelFactor
profile(String, ModelFactor) - Static method in class jdistlib.inference.FactorProfiler
ProfiledModelFactor - Interface in jdistlib.inference: Model factor instrumented with low-overhead call, time, and non-finite counters.
progressListener(ProgressListener) - Method in class jdistlib.inference.SamplingOptions.Builder
progressListener(ReversibleJumpProgressListener) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
progressListener(SparseSubsetProgressListener) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
ProgressListener - Interface in jdistlib.inference: Lightweight callback invoked after a completed sampler transition.
ProjectionPredictiveSelection - Class in jdistlib.inference: Forward projection-predictive variable selection for Gaussian linear reference models.
ProjectionPredictiveSelection.Result - Class in jdistlib.inference
ProjectionPredictiveSelection.Step - Class in jdistlib.inference
propose(ReversibleJumpState, ReversibleJumpTarget, RandomEngine) - Method in interface jdistlib.inference.ReversibleJumpMove
propose(ReversibleJumpState, ReversibleJumpTarget, RandomEngine) - Method in class jdistlib.inference.SubsetBirthMove
propose(ReversibleJumpState, ReversibleJumpTarget, RandomEngine) - Method in class jdistlib.inference.SubsetDeathMove
propose(ReversibleJumpState, ReversibleJumpTarget, RandomEngine) - Method in class jdistlib.inference.SubsetSwapMove
proposedState() - Method in class jdistlib.inference.ReversibleJumpProposal
psave - Variable in class jdistlib.Binomial.RandomState
pseudoObservations(double[][]) - Static method in class jdistlib.CopulaFitter: Converts rectangular raw data to average-rank pseudo-observations.
psi(double) - Static method in class jdistlib.math.MathFunctions: --------------------------------------------------------------------- Evaluation of the Digamma function psi(x) ----------- Psi(xx) is assigned the value 0 when the digamma function cannot be computed.
psigamma(double[], int) - Static method in class jdistlib.math.PolyGamma
psigamma(double, int) - Static method in class jdistlib.math.PolyGamma
PsisLoo - Class in jdistlib.inference: Pareto-smoothed importance-sampling leave-one-out cross-validation.
PsisLoo.ExactLooFallback - Interface in jdistlib.inference: Optional exact or refitted LOO calculation used when importance sampling is unreliable.
PsisLoo.Result - Class in jdistlib.inference
pullback(double[], int, double[], int, double[], double[]) - Method in interface jdistlib.inference.ParameterConstraint: Pulls a constrained gradient back and adds the log-Jacobian gradient.
putPayoff(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk

Q

QMatrixUtils - Class in jdistlib.matrix: Deprecated.
Matrix utilities
QMatrixUtils() - Constructor for class jdistlib.matrix.QMatrixUtils: Deprecated.
qn - Variable in class jdistlib.Binomial.RandomState
QUADPACK - Enum constant in enum class jdistlib.math.IntegrationOptions.Method: QUADPACK DQAGS/DQAGI, matching the historical implementation.
quadraticFormCumulative(double, double[], double, double[][], boolean, boolean) - Static method in class jdistlib.Wishart: CDF of the directional variance event direction' W direction <= upper.
quantile(double) - Method in class jdistlib.generic.GenericDistribution: Assume lower tail and non-log
quantile(double) - Method in class jdistlib.NumericalCdfTable
quantile(double[]) - Method in class jdistlib.generic.GenericDistribution: Assume lower tail and non-log
quantile(double[], boolean, boolean) - Method in class jdistlib.generic.GenericDistribution
quantile(double[], double) - Static method in class jdistlib.math.VectorMath: Find quantile given a sorted data of array (Definition 7)
quantile(double[], double[]) - Static method in class jdistlib.math.VectorMath: Find quantile given a sorted data of array (Definition 7)
quantile(double[], int, int) - Static method in class jdistlib.Ansari
quantile(double[], int, int, double[][][]) - Static method in class jdistlib.Ansari
quantile(double, boolean, boolean) - Method in class jdistlib.Ansari
quantile(double, boolean, boolean) - Method in class jdistlib.Arcsine
quantile(double, boolean, boolean) - Method in class jdistlib.AsymmetricLaplace
quantile(double, boolean, boolean) - Method in class jdistlib.Beta
quantile(double, boolean, boolean) - Method in class jdistlib.BetaBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.BetaNegativeBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.BetaPrime
quantile(double, boolean, boolean) - Method in class jdistlib.Binomial
quantile(double, boolean, boolean) - Method in class jdistlib.BirnbaumSaunders
quantile(double, boolean, boolean) - Method in class jdistlib.Categorical
quantile(double, boolean, boolean) - Method in class jdistlib.Cauchy
quantile(double, boolean, boolean) - Method in class jdistlib.CensoredDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.Chi
quantile(double, boolean, boolean) - Method in class jdistlib.ChiSquare
quantile(double, boolean, boolean) - Method in class jdistlib.DiscreteLaplace
quantile(double, boolean, boolean) - Method in class jdistlib.DiscreteWeibull
quantile(double, boolean, boolean) - Method in class jdistlib.Empirical: Uses the inverse empirical CDF (R quantile type 1).
quantile(double, boolean, boolean) - Method in class jdistlib.evd.Extreme
quantile(double, boolean, boolean) - Method in class jdistlib.evd.Fretchet
quantile(double, boolean, boolean) - Method in class jdistlib.evd.GeneralizedPareto
quantile(double, boolean, boolean) - Method in class jdistlib.evd.GEV
quantile(double, boolean, boolean) - Method in class jdistlib.evd.Gumbel
quantile(double, boolean, boolean) - Method in class jdistlib.evd.Order
quantile(double, boolean, boolean) - Method in class jdistlib.evd.Rayleigh
quantile(double, boolean, boolean) - Method in class jdistlib.evd.ReverseWeibull
quantile(double, boolean, boolean) - Method in class jdistlib.Exponential
quantile(double, boolean, boolean) - Method in class jdistlib.ExponentiallyModifiedGaussian
quantile(double, boolean, boolean) - Method in class jdistlib.F
quantile(double, boolean, boolean) - Method in class jdistlib.FellerPareto
quantile(double, boolean, boolean) - Method in class jdistlib.finance.ConditionalDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.DelaporteDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.EmpiricalDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.FiniteGridDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.OptionImpliedDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.OrderStatisticDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.PolyaAeppliDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.PositiveTemperedStableDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.StableDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.CgmyDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.LevyIncrementDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.MeixnerDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.NormalTemperedStableDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.finance.VarianceGammaDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.FoldedNormal
quantile(double, boolean, boolean) - Method in class jdistlib.Gamma
quantile(double, boolean, boolean) - Method in class jdistlib.GeneralizedBetaSecondKind
quantile(double, boolean, boolean) - Method in class jdistlib.GeneralizedF
quantile(double, boolean, boolean) - Method in class jdistlib.GeneralizedGamma
quantile(double, boolean, boolean) - Method in class jdistlib.generic.GenericDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.Geometric
quantile(double, boolean, boolean) - Method in class jdistlib.Gompertz
quantile(double, boolean, boolean) - Method in class jdistlib.HalfCauchy
quantile(double, boolean, boolean) - Method in class jdistlib.HalfNormal
quantile(double, boolean, boolean) - Method in class jdistlib.HalfT
quantile(double, boolean, boolean) - Method in class jdistlib.Huber
quantile(double, boolean, boolean) - Method in class jdistlib.HurdleNegativeBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.HurdlePoisson
quantile(double, boolean, boolean) - Method in class jdistlib.HyperGeometric
quantile(double, boolean, boolean) - Method in class jdistlib.InvGamma
quantile(double, boolean, boolean) - Method in class jdistlib.InvNormal
quantile(double, boolean, boolean) - Method in class jdistlib.Kendall
quantile(double, boolean, boolean) - Method in class jdistlib.Kumaraswamy
quantile(double, boolean, boolean) - Method in class jdistlib.Laplace
quantile(double, boolean, boolean) - Method in class jdistlib.Levy
quantile(double, boolean, boolean) - Method in class jdistlib.Lindley
quantile(double, boolean, boolean) - Method in class jdistlib.Logarithmic
quantile(double, boolean, boolean) - Method in class jdistlib.Logistic
quantile(double, boolean, boolean) - Method in class jdistlib.LogitNormal
quantile(double, boolean, boolean) - Method in class jdistlib.LogLogistic
quantile(double, boolean, boolean) - Method in class jdistlib.LogNormal
quantile(double, boolean, boolean) - Method in class jdistlib.Makeham
quantile(double, boolean, boolean) - Method in class jdistlib.Maxwell
quantile(double, boolean, boolean) - Method in class jdistlib.MaxwellBoltzmann
quantile(double, boolean, boolean) - Method in class jdistlib.MixtureDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.MonotoneTransformDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.Nakagami
quantile(double, boolean, boolean) - Method in class jdistlib.NegativeHypergeometric
quantile(double, boolean, boolean) - Method in class jdistlib.NegBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.NonCentralBeta
quantile(double, boolean, boolean) - Method in class jdistlib.NonCentralChiSquare
quantile(double, boolean, boolean) - Method in class jdistlib.NonCentralF
quantile(double, boolean, boolean) - Method in class jdistlib.NonCentralT
quantile(double, boolean, boolean) - Method in class jdistlib.Normal
quantile(double, boolean, boolean) - Method in class jdistlib.NumericalContinuousDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.NumericalDiscreteDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.NumericalPiecewiseDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.PhaseType
quantile(double, boolean, boolean) - Method in class jdistlib.Poisson
quantile(double, boolean, boolean) - Method in class jdistlib.PoissonBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.PoissonInverseGaussian
quantile(double, boolean, boolean) - Method in class jdistlib.PositiveNormal
quantile(double, boolean, boolean) - Method in class jdistlib.Rice
quantile(double, boolean, boolean) - Method in class jdistlib.SignRank
quantile(double, boolean, boolean) - Method in class jdistlib.SinhArcsinh
quantile(double, boolean, boolean) - Method in class jdistlib.Skellam
quantile(double, boolean, boolean) - Method in class jdistlib.SkewedT
quantile(double, boolean, boolean) - Method in class jdistlib.Slash
quantile(double, boolean, boolean) - Method in class jdistlib.Spearman: Uses numerical optimization to get approximate value, then followed by manual search.
quantile(double, boolean, boolean) - Method in class jdistlib.T
quantile(double, boolean, boolean) - Method in class jdistlib.Triangular
quantile(double, boolean, boolean) - Method in class jdistlib.TruncatedContinuousDistribution
quantile(double, boolean, boolean) - Method in class jdistlib.Tukey
quantile(double, boolean, boolean) - Method in class jdistlib.TukeyLambda
quantile(double, boolean, boolean) - Method in class jdistlib.Tweedie
quantile(double, boolean, boolean) - Method in class jdistlib.Uniform
quantile(double, boolean, boolean) - Method in class jdistlib.Weibull
quantile(double, boolean, boolean) - Method in class jdistlib.Wilcoxon
quantile(double, boolean, boolean) - Method in class jdistlib.ZeroInflatedNegativeBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.ZeroInflatedPoisson
quantile(double, boolean, boolean) - Method in class jdistlib.ZeroTruncatedNegativeBinomial
quantile(double, boolean, boolean) - Method in class jdistlib.ZeroTruncatedPoisson
quantile(double, boolean, boolean) - Method in class jdistlib.Zipf
quantile(double, double[], boolean, boolean) - Static method in class jdistlib.PoissonBinomial
quantile(double, double[], double[][], boolean, boolean) - Static method in class jdistlib.PhaseType
quantile(double, double[], double[], boolean, boolean) - Static method in class jdistlib.Categorical
quantile(double, double, boolean) - Static method in class jdistlib.evd.Rayleigh
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Chi
quantile(double, double, boolean, boolean) - Static method in class jdistlib.ChiSquare
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Exponential
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Geometric
quantile(double, double, boolean, boolean) - Static method in class jdistlib.HalfCauchy
quantile(double, double, boolean, boolean) - Static method in class jdistlib.HalfNormal
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Lindley
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Logarithmic
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Maxwell
quantile(double, double, boolean, boolean) - Static method in class jdistlib.MaxwellBoltzmann
quantile(double, double, boolean, boolean) - Static method in class jdistlib.Poisson
quantile(double, double, boolean, boolean) - Static method in class jdistlib.T
quantile(double, double, boolean, boolean) - Static method in class jdistlib.TukeyLambda
quantile(double, double, boolean, boolean) - Static method in class jdistlib.ZeroTruncatedPoisson
quantile(double, double, boolean, boolean, int) - Static method in class jdistlib.Logarithmic
quantile(double, double, double, boolean) - Static method in class jdistlib.evd.Gumbel
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Arcsine: Quantile method by bisection
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Beta
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.BetaPrime
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Binomial
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Cauchy
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.DiscreteLaplace
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.DiscreteWeibull
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.F
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Gamma
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Gompertz
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.HalfT
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.HurdlePoisson
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.InvGamma
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.InvNormal
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Kumaraswamy
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Laplace
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Levy
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Logistic
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.LogitNormal
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.LogLogistic
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.LogNormal
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Nakagami
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.NegBinomial
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralChiSquare
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralT
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Normal
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.PoissonInverseGaussian
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.PositiveNormal
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Rice
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Skellam
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.SkewedT
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Slash
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Uniform
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.Weibull
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.ZeroInflatedPoisson
quantile(double, double, double, boolean, boolean) - Static method in class jdistlib.ZeroTruncatedNegativeBinomial
quantile(double, double, double, double, boolean) - Static method in class jdistlib.evd.Fretchet
quantile(double, double, double, double, boolean) - Static method in class jdistlib.evd.GeneralizedPareto
quantile(double, double, double, double, boolean) - Static method in class jdistlib.evd.GEV
quantile(double, double, double, double, boolean) - Static method in class jdistlib.evd.ReverseWeibull
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.AsymmetricLaplace
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.BetaBinomial: Quantile.
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.BetaNegativeBinomial
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.BirnbaumSaunders
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.ExponentiallyModifiedGaussian
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.GeneralizedGamma
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Huber
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.HurdleNegativeBinomial
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.HyperGeometric
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Makeham
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.NegativeHypergeometric
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralBeta
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.NonCentralF
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Triangular
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Tukey: Copenhaver, Margaret Diponzio & Holland, Burt S.
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.Tweedie: Returns a Tweedie quantile.
quantile(double, double, double, double, boolean, boolean) - Static method in class jdistlib.ZeroInflatedNegativeBinomial
quantile(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.FoldedNormal
quantile(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.GeneralizedBetaSecondKind
quantile(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.GeneralizedF
quantile(double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.SinhArcsinh
quantile(double, double, double, double, double, double, boolean, boolean) - Static method in class jdistlib.FellerPareto
quantile(double, int) - Static method in class jdistlib.Kendall: Quantile search.
quantile(double, int, boolean, boolean) - Static method in class jdistlib.Spearman: Uses bisection.
quantile(double, int, double, boolean, boolean) - Static method in class jdistlib.Zipf
quantile(double, int, int) - Static method in class jdistlib.Ansari
quantile(double, int, int, double[][][]) - Static method in class jdistlib.Ansari
quantile(double, GenericDistribution, int, boolean, boolean) - Static method in class jdistlib.evd.Extreme
quantile(double, GenericDistribution, int, int, boolean, boolean, boolean) - Static method in class jdistlib.evd.Order: Find the quantile of order statistics.
quantile_mu(double, double, double, boolean, boolean) - Static method in class jdistlib.NegBinomial
quantile_tau(double, int) - Static method in class jdistlib.Kendall
quantile0(double[], double) - Static method in class jdistlib.math.VectorMath: Find quantile in an array (Definition 7).
quantile0(double[], double[]) - Static method in class jdistlib.math.VectorMath: Find quantile in an array (Definition 7).
quantileInto(double[], int, double[], int, int, boolean, boolean) - Method in class jdistlib.generic.GenericDistribution: Evaluates quantiles into caller-owned storage.
quantileMcse(double[], double) - Static method in class jdistlib.inference.MonteCarloError
qValues(double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes Storey q-values using the default smoothing-spline estimate of the true-null proportion.
qValues(double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Computes Storey q-values for a caller-supplied true-null proportion.
qValues(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Computes Storey q-values with caller-controlled spline settings.
qValuesQuantile(double[]) - Static method in class jdistlib.disttest.MultipleTesting: Computes q-values using the default 0.10 quantile pi-zero estimate.
qValuesQuantile(double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Computes q-values using the quantile-based estimate of pi-zero.
qValuesQuantile(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Computes quantile-estimated q-values with a caller-supplied lambda grid.

R

r - Variable in class jdistlib.HyperGeometric
radialQuantile(double, int, boolean, boolean) - Static method in class jdistlib.MultivariateCauchy
radialQuantile(double, int, boolean, boolean) - Static method in class jdistlib.MultivariateNormal: Quantile of the Mahalanobis radius containing probability p.
radialQuantile(double, int, double, boolean, boolean) - Static method in class jdistlib.MultivariatePowerExponential: Quantile of the scatter-standardized radial distance.
radialQuantile(double, int, double, boolean, boolean) - Static method in class jdistlib.MultivariateStudentT: Quantile of the Mahalanobis radius containing probability p.
random - Variable in class jdistlib.generic.GenericDistribution
random() - Method in class jdistlib.Ansari
random() - Method in class jdistlib.Arcsine
random() - Method in class jdistlib.AsymmetricLaplace
random() - Method in class jdistlib.Beta
random() - Method in class jdistlib.BetaBinomial
random() - Method in class jdistlib.BetaNegativeBinomial
random() - Method in class jdistlib.BetaPrime
random() - Method in class jdistlib.Binomial
random() - Method in class jdistlib.BirnbaumSaunders
random() - Method in class jdistlib.Categorical
random() - Method in class jdistlib.Cauchy
random() - Method in class jdistlib.CensoredDistribution
random() - Method in class jdistlib.CertifiedInfiniteDiscreteDistribution
random() - Method in class jdistlib.Chi
random() - Method in class jdistlib.ChiSquare
random() - Method in class jdistlib.DiscreteLaplace
random() - Method in class jdistlib.DiscreteWeibull
random() - Method in class jdistlib.Empirical
random() - Method in class jdistlib.evd.Extreme
random() - Method in class jdistlib.evd.Fretchet
random() - Method in class jdistlib.evd.GeneralizedPareto
random() - Method in class jdistlib.evd.GEV
random() - Method in class jdistlib.evd.Gumbel
random() - Method in class jdistlib.evd.Order
random() - Method in class jdistlib.evd.Rayleigh
random() - Method in class jdistlib.evd.ReverseWeibull
random() - Method in class jdistlib.Exponential
random() - Method in class jdistlib.ExponentiallyModifiedGaussian
random() - Method in class jdistlib.F
random() - Method in class jdistlib.FellerPareto
random() - Method in class jdistlib.finance.ConditionalDistribution
random() - Method in class jdistlib.finance.DelaporteDistribution
random() - Method in class jdistlib.finance.EmpiricalDistribution
random() - Method in class jdistlib.finance.FiniteGridDistribution
random() - Method in class jdistlib.finance.GeneralizedHyperbolicDistribution
random() - Method in class jdistlib.finance.GeneralizedInverseGaussianDistribution
random() - Method in class jdistlib.finance.OptionImpliedDistribution
random() - Method in class jdistlib.finance.OrderStatisticDistribution
random() - Method in class jdistlib.finance.PolyaAeppliDistribution
random() - Method in class jdistlib.finance.StableDistribution
random() - Method in class jdistlib.finance.CgmyDistribution
random() - Method in class jdistlib.finance.LevyIncrementDistribution
random() - Method in class jdistlib.finance.MeixnerDistribution
random() - Method in class jdistlib.finance.NormalTemperedStableDistribution
random() - Method in class jdistlib.finance.PositiveTemperedStableDistribution
random() - Method in class jdistlib.finance.VarianceGammaDistribution
random() - Method in class jdistlib.FoldedNormal
random() - Method in class jdistlib.Gamma
random() - Method in class jdistlib.GeneralizedBetaSecondKind
random() - Method in class jdistlib.GeneralizedF
random() - Method in class jdistlib.GeneralizedGamma
random() - Method in class jdistlib.generic.GenericDistribution
random() - Method in class jdistlib.Geometric
random() - Method in class jdistlib.Gompertz
random() - Method in class jdistlib.HalfCauchy
random() - Method in class jdistlib.HalfNormal
random() - Method in class jdistlib.HalfT
random() - Method in class jdistlib.Huber
random() - Method in class jdistlib.HurdleNegativeBinomial
random() - Method in class jdistlib.HurdlePoisson
random() - Method in class jdistlib.HyperGeometric
random() - Method in class jdistlib.inference.ChainCheckpoint
random() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
random() - Method in class jdistlib.inference.SparseSubsetCheckpoint
random() - Method in class jdistlib.InvGamma
random() - Method in class jdistlib.InvNormal
random() - Method in class jdistlib.Kendall
random() - Method in class jdistlib.Kumaraswamy
random() - Method in class jdistlib.Laplace
random() - Method in class jdistlib.Levy
random() - Method in class jdistlib.Lindley
random() - Method in class jdistlib.Logarithmic
random() - Method in class jdistlib.Logistic
random() - Method in class jdistlib.LogitNormal
random() - Method in class jdistlib.LogLogistic
random() - Method in class jdistlib.LogNormal
random() - Method in class jdistlib.Makeham
random() - Method in class jdistlib.Maxwell
random() - Method in class jdistlib.MaxwellBoltzmann
random() - Method in class jdistlib.MixtureDistribution
random() - Method in class jdistlib.MonotoneTransformDistribution
random() - Method in class jdistlib.Nakagami
random() - Method in class jdistlib.NegativeHypergeometric
random() - Method in class jdistlib.NegBinomial
random() - Method in class jdistlib.NonCentralBeta
random() - Method in class jdistlib.NonCentralChiSquare
random() - Method in class jdistlib.NonCentralF
random() - Method in class jdistlib.NonCentralT
random() - Method in class jdistlib.Normal
random() - Method in class jdistlib.NumericalContinuousDistribution
random() - Method in class jdistlib.NumericalDiscreteDistribution
random() - Method in class jdistlib.NumericalPiecewiseDistribution
random() - Method in class jdistlib.PhaseType
random() - Method in class jdistlib.Poisson
random() - Method in class jdistlib.PoissonBinomial
random() - Method in class jdistlib.PoissonInverseGaussian
random() - Method in class jdistlib.PositiveNormal
random() - Method in class jdistlib.Rice
random() - Method in class jdistlib.rng.RandomEngine
random() - Method in class jdistlib.SignRank
random() - Method in class jdistlib.SinhArcsinh
random() - Method in class jdistlib.Skellam
random() - Method in class jdistlib.SkewedT
random() - Method in class jdistlib.Slash
random() - Method in class jdistlib.Spearman: Inverse CDF lookup
random() - Method in class jdistlib.T
random() - Method in class jdistlib.Triangular
random() - Method in class jdistlib.TruncatedContinuousDistribution
random() - Method in class jdistlib.Tukey
random() - Method in class jdistlib.TukeyLambda
random() - Method in class jdistlib.Tweedie
random() - Method in class jdistlib.Uniform
random() - Method in class jdistlib.Weibull
random() - Method in class jdistlib.Wilcoxon
random() - Method in class jdistlib.ZeroInflatedNegativeBinomial
random() - Method in class jdistlib.ZeroInflatedPoisson
random() - Method in class jdistlib.ZeroTruncatedNegativeBinomial
random() - Method in class jdistlib.ZeroTruncatedPoisson
random() - Method in class jdistlib.Zipf
random(double[], double[][], double, RandomEngine) - Static method in class jdistlib.MultivariatePowerExponential
random(double[], double[][], double, RandomEngine) - Static method in class jdistlib.MultivariateStudentT
random(double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateCauchy
random(double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateLaplace
random(double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateLogNormal
random(double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateNormal
random(double[], double[][], RandomEngine) - Static method in class jdistlib.PhaseType
random(double[], double[], RandomEngine) - Static method in class jdistlib.Categorical
random(double[], RandomEngine) - Static method in class jdistlib.Dirichlet
random(double[], RandomEngine) - Static method in class jdistlib.Empirical
random(double[], RandomEngine) - Static method in class jdistlib.PoissonBinomial
random(double, double[][], RandomEngine) - Static method in class jdistlib.Wishart: Generates one Wishart matrix using Bartlett's decomposition.
random(double, double, double, double, double, RandomEngine) - Static method in class jdistlib.FellerPareto
random(double, double, double, double, RandomEngine) - Static method in class jdistlib.BivariateLogistic
random(double, double, double, double, RandomEngine) - Static method in class jdistlib.FoldedNormal
random(double, double, double, double, RandomEngine) - Static method in class jdistlib.GeneralizedBetaSecondKind
random(double, double, double, double, RandomEngine) - Static method in class jdistlib.GeneralizedF
random(double, double, double, double, RandomEngine) - Static method in class jdistlib.SinhArcsinh
random(double, double, double, double, RandomEngine) - Static method in class jdistlib.Wiener: Draws a first-passage time conditional on the modeled upper response.
random(double, double, double, RandomEngine) - Static method in class jdistlib.AsymmetricLaplace
random(double, double, double, RandomEngine) - Static method in class jdistlib.BetaBinomial: Random variate
random(double, double, double, RandomEngine) - Static method in class jdistlib.BetaNegativeBinomial
random(double, double, double, RandomEngine) - Static method in class jdistlib.BirnbaumSaunders
random(double, double, double, RandomEngine) - Static method in class jdistlib.BivariatePoisson
random(double, double, double, RandomEngine) - Static method in class jdistlib.evd.Fretchet
random(double, double, double, RandomEngine) - Static method in class jdistlib.evd.GeneralizedPareto
random(double, double, double, RandomEngine) - Static method in class jdistlib.evd.GEV
random(double, double, double, RandomEngine) - Static method in class jdistlib.evd.ReverseWeibull
random(double, double, double, RandomEngine) - Static method in class jdistlib.ExponentiallyModifiedGaussian
random(double, double, double, RandomEngine) - Static method in class jdistlib.GeneralizedGamma
random(double, double, double, RandomEngine) - Static method in class jdistlib.Huber
random(double, double, double, RandomEngine) - Static method in class jdistlib.HurdleNegativeBinomial
random(double, double, double, RandomEngine) - Static method in class jdistlib.HyperGeometric
random(double, double, double, RandomEngine) - Static method in class jdistlib.Makeham
random(double, double, double, RandomEngine) - Static method in class jdistlib.NonCentralBeta
random(double, double, double, RandomEngine) - Static method in class jdistlib.NonCentralF
random(double, double, double, RandomEngine) - Static method in class jdistlib.Triangular
random(double, double, double, RandomEngine) - Static method in class jdistlib.Tukey: Tukey RNG by inversion -- WARNING: Untested
random(double, double, double, RandomEngine) - Static method in class jdistlib.Tweedie: Generates one Tweedie variate using the supplied random engine.
random(double, double, double, RandomEngine) - Static method in class jdistlib.ZeroInflatedNegativeBinomial
random(double, double, double, RandomEngine, HyperGeometric.RandomState) - Static method in class jdistlib.HyperGeometric
random(double, double, RandomEngine) - Static method in class jdistlib.Arcsine
random(double, double, RandomEngine) - Static method in class jdistlib.Beta
random(double, double, RandomEngine) - Static method in class jdistlib.BetaPrime
random(double, double, RandomEngine) - Static method in class jdistlib.Binomial
random(double, double, RandomEngine) - Static method in class jdistlib.Cauchy
random(double, double, RandomEngine) - Static method in class jdistlib.DiscreteLaplace
random(double, double, RandomEngine) - Static method in class jdistlib.DiscreteWeibull
random(double, double, RandomEngine) - Static method in class jdistlib.evd.Gumbel
random(double, double, RandomEngine) - Static method in class jdistlib.F
random(double, double, RandomEngine) - Static method in class jdistlib.Gamma
random(double, double, RandomEngine) - Static method in class jdistlib.Gompertz
random(double, double, RandomEngine) - Static method in class jdistlib.HalfT
random(double, double, RandomEngine) - Static method in class jdistlib.HurdlePoisson
random(double, double, RandomEngine) - Static method in class jdistlib.InvGamma
random(double, double, RandomEngine) - Static method in class jdistlib.InvNormal
random(double, double, RandomEngine) - Static method in class jdistlib.Kumaraswamy
random(double, double, RandomEngine) - Static method in class jdistlib.Laplace
random(double, double, RandomEngine) - Static method in class jdistlib.Levy: Random by quantile inversion -- the default in R
random(double, double, RandomEngine) - Static method in class jdistlib.Logistic
random(double, double, RandomEngine) - Static method in class jdistlib.LogitNormal
random(double, double, RandomEngine) - Static method in class jdistlib.LogLogistic
random(double, double, RandomEngine) - Static method in class jdistlib.LogNormal
random(double, double, RandomEngine) - Static method in class jdistlib.Nakagami
random(double, double, RandomEngine) - Static method in class jdistlib.NegBinomial
random(double, double, RandomEngine) - Static method in class jdistlib.NonCentralChiSquare: According to Hans R.
random(double, double, RandomEngine) - Static method in class jdistlib.NonCentralT
random(double, double, RandomEngine) - Static method in class jdistlib.Normal: Random normal by quantile inversion -- the default in R
random(double, double, RandomEngine) - Static method in class jdistlib.PoissonInverseGaussian
random(double, double, RandomEngine) - Static method in class jdistlib.PositiveNormal
random(double, double, RandomEngine) - Static method in class jdistlib.Rice
random(double, double, RandomEngine) - Static method in class jdistlib.Skellam
random(double, double, RandomEngine) - Static method in class jdistlib.SkewedT
random(double, double, RandomEngine) - Static method in class jdistlib.Slash
random(double, double, RandomEngine) - Static method in class jdistlib.Uniform
random(double, double, RandomEngine) - Static method in class jdistlib.Weibull
random(double, double, RandomEngine) - Static method in class jdistlib.ZeroInflatedPoisson
random(double, double, RandomEngine) - Static method in class jdistlib.ZeroTruncatedNegativeBinomial
random(double, double, RandomEngine, Binomial.RandomState) - Static method in class jdistlib.Binomial
random(double, RandomEngine) - Static method in class jdistlib.Chi
random(double, RandomEngine) - Static method in class jdistlib.ChiSquare
random(double, RandomEngine) - Static method in class jdistlib.evd.Rayleigh
random(double, RandomEngine) - Static method in class jdistlib.Exponential
random(double, RandomEngine) - Static method in class jdistlib.Geometric
random(double, RandomEngine) - Static method in class jdistlib.HalfCauchy
random(double, RandomEngine) - Static method in class jdistlib.HalfNormal
random(double, RandomEngine) - Static method in class jdistlib.Lindley
random(double, RandomEngine) - Static method in class jdistlib.Logarithmic
random(double, RandomEngine) - Static method in class jdistlib.Maxwell
random(double, RandomEngine) - Static method in class jdistlib.MaxwellBoltzmann
random(double, RandomEngine) - Static method in class jdistlib.Poisson
random(double, RandomEngine) - Static method in class jdistlib.T
random(double, RandomEngine) - Static method in class jdistlib.TukeyLambda
random(double, RandomEngine) - Static method in class jdistlib.ZeroTruncatedPoisson
random(double, RandomEngine, Poisson.RandomState) - Static method in class jdistlib.Poisson
random(int) - Method in class jdistlib.Binomial
random(int) - Method in class jdistlib.generic.GenericDistribution
random(int) - Method in class jdistlib.HyperGeometric
random(int) - Method in class jdistlib.Poisson
random(int[], int, RandomEngine) - Static method in class jdistlib.MultivariateHypergeometric
random(int, double[], double[][], double, RandomEngine) - Static method in class jdistlib.MultivariatePowerExponential
random(int, double[], double[][], double, RandomEngine) - Static method in class jdistlib.MultivariateStudentT
random(int, double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateCauchy
random(int, double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateLaplace
random(int, double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateLogNormal
random(int, double[], double[][], RandomEngine) - Static method in class jdistlib.MultivariateNormal
random(int, double[], double[], RandomEngine) - Static method in class jdistlib.Categorical
random(int, double[], RandomEngine) - Static method in class jdistlib.Dirichlet
random(int, double[], RandomEngine) - Static method in class jdistlib.DirichletMultinomial
random(int, double[], RandomEngine) - Static method in class jdistlib.Empirical
random(int, double[], RandomEngine) - Static method in class jdistlib.Multinomial
random(int, double[], RandomEngine) - Static method in class jdistlib.PoissonBinomial
random(int, double[], RandomEngine, Binomial.RandomState) - Static method in class jdistlib.Multinomial: Draws a multinomial vector using sequential conditional binomials and Kahan compensated probability arithmetic, matching current R's rmultinom.
random(int, double, double[][], RandomEngine) - Static method in class jdistlib.Wishart: Generates count matrices while retaining one caller-owned RNG.
random(int, double, double, double, double, RandomEngine) - Static method in class jdistlib.BivariateLogistic
random(int, double, double, double, double, RandomEngine) - Static method in class jdistlib.FoldedNormal
random(int, double, double, double, double, RandomEngine) - Static method in class jdistlib.GeneralizedBetaSecondKind
random(int, double, double, double, double, RandomEngine) - Static method in class jdistlib.SinhArcsinh
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.BetaBinomial
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.BirnbaumSaunders
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.BivariatePoisson
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.evd.Fretchet
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.evd.GeneralizedPareto
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.evd.GEV
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.evd.ReverseWeibull
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.GeneralizedGamma
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.HurdleNegativeBinomial
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.HyperGeometric
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.Makeham
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.NonCentralBeta
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.NonCentralF
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.Triangular
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.Tukey
random(int, double, double, double, RandomEngine) - Static method in class jdistlib.ZeroInflatedNegativeBinomial
random(int, double, double, double, RandomEngine, HyperGeometric.RandomState) - Static method in class jdistlib.HyperGeometric
random(int, double, double, RandomEngine) - Static method in class jdistlib.Arcsine
random(int, double, double, RandomEngine) - Static method in class jdistlib.Beta
random(int, double, double, RandomEngine) - Static method in class jdistlib.Binomial
random(int, double, double, RandomEngine) - Static method in class jdistlib.Cauchy
random(int, double, double, RandomEngine) - Static method in class jdistlib.DiscreteLaplace
random(int, double, double, RandomEngine) - Static method in class jdistlib.evd.Gumbel
random(int, double, double, RandomEngine) - Static method in class jdistlib.F
random(int, double, double, RandomEngine) - Static method in class jdistlib.Gamma
random(int, double, double, RandomEngine) - Static method in class jdistlib.Gompertz
random(int, double, double, RandomEngine) - Static method in class jdistlib.HurdlePoisson
random(int, double, double, RandomEngine) - Static method in class jdistlib.InvGamma
random(int, double, double, RandomEngine) - Static method in class jdistlib.InvNormal
random(int, double, double, RandomEngine) - Static method in class jdistlib.Kumaraswamy
random(int, double, double, RandomEngine) - Static method in class jdistlib.Laplace
random(int, double, double, RandomEngine) - Static method in class jdistlib.Levy
random(int, double, double, RandomEngine) - Static method in class jdistlib.Logistic
random(int, double, double, RandomEngine) - Static method in class jdistlib.LogLogistic
random(int, double, double, RandomEngine) - Static method in class jdistlib.LogNormal
random(int, double, double, RandomEngine) - Static method in class jdistlib.Nakagami
random(int, double, double, RandomEngine) - Static method in class jdistlib.NegBinomial
random(int, double, double, RandomEngine) - Static method in class jdistlib.NonCentralChiSquare
random(int, double, double, RandomEngine) - Static method in class jdistlib.NonCentralT
random(int, double, double, RandomEngine) - Static method in class jdistlib.Normal
random(int, double, double, RandomEngine) - Static method in class jdistlib.PoissonInverseGaussian
random(int, double, double, RandomEngine) - Static method in class jdistlib.PositiveNormal
random(int, double, double, RandomEngine) - Static method in class jdistlib.Rice
random(int, double, double, RandomEngine) - Static method in class jdistlib.SkewedT
random(int, double, double, RandomEngine) - Static method in class jdistlib.Uniform
random(int, double, double, RandomEngine) - Static method in class jdistlib.Weibull
random(int, double, double, RandomEngine) - Static method in class jdistlib.ZeroInflatedPoisson
random(int, double, double, RandomEngine) - Static method in class jdistlib.ZeroTruncatedNegativeBinomial
random(int, double, double, RandomEngine, Binomial.RandomState) - Static method in class jdistlib.Binomial
random(int, double, RandomEngine) - Static method in class jdistlib.Chi
random(int, double, RandomEngine) - Static method in class jdistlib.ChiSquare
random(int, double, RandomEngine) - Static method in class jdistlib.evd.Rayleigh
random(int, double, RandomEngine) - Static method in class jdistlib.Exponential
random(int, double, RandomEngine) - Static method in class jdistlib.Geometric
random(int, double, RandomEngine) - Static method in class jdistlib.HalfNormal
random(int, double, RandomEngine) - Static method in class jdistlib.Lindley
random(int, double, RandomEngine) - Static method in class jdistlib.Logarithmic
random(int, double, RandomEngine) - Static method in class jdistlib.Maxwell
random(int, double, RandomEngine) - Static method in class jdistlib.MaxwellBoltzmann
random(int, double, RandomEngine) - Static method in class jdistlib.Poisson
random(int, double, RandomEngine) - Static method in class jdistlib.T
random(int, double, RandomEngine) - Static method in class jdistlib.ZeroTruncatedPoisson
random(int, double, RandomEngine) - Static method in class jdistlib.Zipf
random(int, double, RandomEngine, Poisson.RandomState) - Static method in class jdistlib.Poisson
random(int, int[], int, RandomEngine) - Static method in class jdistlib.MultivariateHypergeometric
random(int, int, double[][][], RandomEngine) - Static method in class jdistlib.Ansari
random(int, int, double[], RandomEngine) - Static method in class jdistlib.DirichletMultinomial
random(int, int, double[], RandomEngine) - Static method in class jdistlib.Multinomial
random(int, int, double[], RandomEngine, Binomial.RandomState) - Static method in class jdistlib.Multinomial
random(int, int, double, RandomEngine) - Static method in class jdistlib.Zipf
random(int, int, int, double[][][], RandomEngine) - Static method in class jdistlib.Ansari
random(int, int, int, RandomEngine) - Static method in class jdistlib.Ansari
random(int, int, int, RandomEngine) - Static method in class jdistlib.NegativeHypergeometric
random(int, int, RandomEngine) - Static method in class jdistlib.Ansari: Ansari RNG by inversion -- WARNING: Untested
random(int, int, RandomEngine) - Static method in class jdistlib.Kendall
random(int, int, RandomEngine) - Static method in class jdistlib.Spearman
random(int, long) - Method in interface jdistlib.Copula: Generates count vectors using a new deterministic stream.
random(int, long) - Method in class jdistlib.CopulaDistribution: Generates observations using a new deterministic stream.
random(int, long) - Method in class jdistlib.MixedCopulaDistribution
random(int, GenericDistribution, int, boolean, RandomEngine) - Static method in class jdistlib.evd.Extreme
random(int, GenericDistribution, int, int, boolean, RandomEngine) - Static method in class jdistlib.evd.Order
random(int, RandomEngine) - Method in interface jdistlib.Copula: Generates count vectors from one stream.
random(int, RandomEngine) - Method in class jdistlib.CopulaDistribution: Generates observations from one stream.
random(int, RandomEngine) - Static method in class jdistlib.Kendall: Kendall RNG by inversion
random(int, RandomEngine) - Method in class jdistlib.MixedCopulaDistribution
random(int, RandomEngine) - Method in class jdistlib.SignRank
random(int, RandomEngine) - Static method in class jdistlib.Spearman: Inverse CDF lookup
random(long) - Method in interface jdistlib.Copula: Generates one vector using a new deterministic stream.
random(long) - Method in class jdistlib.CopulaDistribution: Generates one observation using a new deterministic stream.
random(long) - Method in class jdistlib.finance.MultivariateFinancialDistribution
random(long) - Method in class jdistlib.MixedCopulaDistribution
random(GenericDistribution, int, boolean, RandomEngine) - Static method in class jdistlib.evd.Extreme
random(GenericDistribution, int, int, boolean, RandomEngine) - Static method in class jdistlib.evd.Order
random(RejectionEnvelope, int) - Method in class jdistlib.NumericalContinuousDistribution: Draws one value using an explicit rejection envelope.
random(RandomEngine) - Method in class jdistlib.BB1Copula
random(RandomEngine) - Method in class jdistlib.ClaytonCopula
random(RandomEngine) - Method in interface jdistlib.Copula: Generates one vector of dependent uniform variates.
random(RandomEngine) - Method in class jdistlib.CopulaDistribution: Generates one joint observation.
random(RandomEngine) - Method in class jdistlib.CVineCopula
random(RandomEngine) - Method in class jdistlib.DVineCopula
random(RandomEngine) - Method in class jdistlib.finance.MultivariateFinancialDistribution
random(RandomEngine) - Method in class jdistlib.FrankCopula
random(RandomEngine) - Method in class jdistlib.GaussianCopula
random(RandomEngine) - Method in class jdistlib.generic.GenericDistribution: Deprecated.
random(RandomEngine) - Method in class jdistlib.GumbelCopula
random(RandomEngine) - Method in class jdistlib.IndependenceCopula
random(RandomEngine) - Method in interface jdistlib.inference.GaussianReference
random(RandomEngine) - Method in class jdistlib.JoeCopula
random(RandomEngine) - Method in class jdistlib.MixedCopulaDistribution
random(RandomEngine) - Method in class jdistlib.RotatedCopula
random(RandomEngine) - Method in class jdistlib.SignRank: Deprecated.
random(RandomEngine) - Method in class jdistlib.StudentTCopula
random_ahrens_dieter(double, double, RandomEngine) - Static method in class jdistlib.Normal
random_box_muller(double, double, RandomEngine) - Static method in class jdistlib.Normal
random_kinderman_ramage(double, double, RandomEngine) - Static method in class jdistlib.Normal
random_mu(double, double, RandomEngine) - Static method in class jdistlib.NegBinomial
random_mu(int, double, double, RandomEngine) - Static method in class jdistlib.NegBinomial
random_standard(int, RandomEngine) - Static method in class jdistlib.Exponential
random_standard(int, RandomEngine) - Static method in class jdistlib.Normal
random_standard(RandomEngine) - Static method in class jdistlib.Exponential
random_standard(RandomEngine) - Static method in class jdistlib.Levy
random_standard(RandomEngine) - Static method in class jdistlib.Normal
RandomCMWC - Class in jdistlib.rng: Implementation of CMWC4096 (Complementary-multiply-with-carry) random number generator by George Marsaglia.
RandomCMWC() - Constructor for class jdistlib.rng.RandomCMWC
RandomEngine - Class in jdistlib.rng
RandomEngine() - Constructor for class jdistlib.rng.RandomEngine
randomFromScale(double, double[][], RandomEngine) - Static method in class jdistlib.Wishart: Convenience generator accepting the scale matrix rather than its factor.
randomFromScale(int, double, double[][], RandomEngine) - Static method in class jdistlib.Wishart
randomInto(double[], int, int) - Method in class jdistlib.generic.GenericDistribution: Generates directly into caller-owned storage.
randomizedProbeBudget(int) - Method in class jdistlib.FunctionAnalysisOptions.Builder: Sets the total randomized sampling budget; zero disables random probes.
RandomSampler - Class in jdistlib.rng: Space and time efficiently computes a sorted Simple Random Sample Without Replacement (SRSWOR), that is, a sorted set of n random numbers from an interval of N numbers; Example: Computing n=3 random numbers from the interval [1,50] may yield the sorted random set (7,13,47).
RandomSampler(long, long, long, RandomEngine) - Constructor for class jdistlib.rng.RandomSampler: Constructs a random sampler that computes and delivers sorted random sets in blocks.
randomSeed(long) - Method in class jdistlib.FunctionAnalysisOptions.Builder
RandomState() - Constructor for class jdistlib.Binomial.RandomState
RandomState() - Constructor for class jdistlib.HyperGeometric.RandomState
RandomState() - Constructor for class jdistlib.Poisson.RandomState
RandomState(Binomial.BinomialKind) - Constructor for class jdistlib.Binomial.RandomState
RandomWalkKernel - Class in jdistlib.inference: Reusable Gaussian random-walk Metropolis transition kernel.
RandomWalkKernel() - Constructor for class jdistlib.inference.RandomWalkKernel
RandomWalkKernel.State - Class in jdistlib.inference
RandomWalkMetropolis - Class in jdistlib.inference: Isotropic Gaussian random-walk Metropolis with warmup scale adaptation.
RandomWalkMetropolis() - Constructor for class jdistlib.inference.RandomWalkMetropolis
RandomWELL44497b - Class in jdistlib.rng: Implementation of WELL 44497b (Well Equidistributed Long-period Linear) random number generator by Francois Panneton, et al.
RandomWELL44497b() - Constructor for class jdistlib.rng.RandomWELL44497b
RandomWELL44497b(int[]) - Constructor for class jdistlib.rng.RandomWELL44497b
range(double[]) - Static method in class jdistlib.math.VectorMath
rank() - Method in class jdistlib.accelerator.FloatPivotedQrFactor
rank() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition: Returns numerical rank using the standard dimension-scaled machine threshold.
rank() - Method in class jdistlib.accelerator.PivotedQrFactor: Estimates numerical rank using max(rows,columns)*ulp(1)*max(abs(diag(R))).
rank() - Method in class jdistlib.accelerator.SingularValueDecomposition: Returns numerical rank using the standard dimension-scaled machine threshold.
rank(double) - Method in class jdistlib.accelerator.PivotedQrFactor: Returns the number of diagonal entries of R larger than an absolute tolerance.
rank(double[]) - Static method in class jdistlib.util.Utilities: Returns the ranks of the elements of array e, resolve ties by averaging
rank(double[], Utilities.RankTies) - Static method in class jdistlib.util.Utilities: Returns the ranks of the elements of array e.
rank(float) - Method in class jdistlib.accelerator.FloatPivotedQrFactor
ranking() - Method in class jdistlib.inference.ShrinkageSelection.Result
ranks(String, int, int, ChainResult...) - Static method in class jdistlib.inference.DiagnosticGraphs
ranks(SimulationBasedCalibration.Generator, Sampler, SamplingOptions, int, long) - Static method in class jdistlib.inference.SimulationBasedCalibration
ratio(GenericDistribution, GenericDistribution, int, long) - Static method in class jdistlib.finance.DistributionAggregation
rawMoment(double) - Method in class jdistlib.NumericalContinuousDistribution: Numerically evaluates E[X^order].
rawMoment(double) - Method in class jdistlib.NumericalDiscreteDistribution
Rayleigh - Class in jdistlib.evd: Rayleigh distribution Taken from VGAM package of R
Rayleigh(double) - Constructor for class jdistlib.evd.Rayleigh
read(Path) - Static method in class jdistlib.inference.ChunkedDrawSink
read(Path) - Static method in class jdistlib.inference.MappedDrawStore
read(Path, String, String) - Static method in class jdistlib.inference.CheckpointIO
read(Path, String, String) - Static method in class jdistlib.inference.ReversibleJumpCheckpointIO
read(Path, String, String) - Static method in class jdistlib.inference.SparseSubsetCheckpointIO
readState(DataInputStream) - Method in class jdistlib.rng.MersenneTwister: Reads the entire state of the MersenneTwister RNG from the stream
readState(DataInputStream) - Method in class jdistlib.rng.MersenneTwisterSafe: Reads the entire state of the MersenneTwister RNG from the stream
real() - Static method in class jdistlib.inference.Constraints
real() - Static method in class jdistlib.inference.CoordinateSupport
real() - Method in class jdistlib.math.Complex
REAL - Enum constant in enum class jdistlib.inference.CoordinateSupport.Kind
realVector(int) - Static method in class jdistlib.inference.Constraints
reason() - Method in class jdistlib.accelerator.ExecutionPlan
rebuildCdfTable(CdfTableOptions) - Method in class jdistlib.NumericalContinuousDistribution: Rebuilds and installs the reusable CDF table with explicit settings.
rec(double[]) - Static method in class jdistlib.util.Utilities
RECTANGLE_DIFFERENCE - Enum constant in enum class jdistlib.CopulaMeasureResult.Status
RECTANGULAR - Enum constant in enum class jdistlib.math.density.Kernel
refactor(CsrMatrix) - Method in interface jdistlib.accelerator.PreparedSparseCholesky: Replaces only numerical values; the authoritative-triangle structure must match.
refactor(FloatCsrMatrix) - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
ReferenceOptions - Class in jdistlib.finance: Reference Black-Scholes/Bachelier transformations and checked inversion.
refinementPasses(int) - Method in class jdistlib.CdfTableOptions.Builder
reject(double[], double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Returns one rejection flag per input, with missing values marked false.
reject(double[], double, MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Returns rejection flags for a declared total family size.
RejectionEnvelope - Interface in jdistlib: Proposal distribution and certified majorization constant for rejection sampling.
rejectionReason() - Method in class jdistlib.inference.ReversibleJumpProposal
rejectionSampling(RejectionEnvelope, int) - Method in class jdistlib.NumericalContinuousDistribution.Builder
rejectLog(double[], double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Returns rejection flags for natural-log p-values.
rejectLog(double[], double, MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Returns log-p rejection flags for a declared total family size.
rejectLogWeightedBenjaminiHochberg(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns weighted-BH rejection flags for natural-log p-values.
rejectLogWeightedBenjaminiYekutieli(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns log-scale weighted-BY rejection flags.
rejectLogWeightedBonferroni(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns log-scale weighted-Bonferroni rejection flags.
rejectLogWeightedHolm(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns log-scale weighted-Holm rejection flags.
rejectMethodD(long, long, int, long, long[], int, RandomEngine) - Static method in class jdistlib.rng.RandomSampler: Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
rejectWeightedBenjaminiHochberg(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns weighted-BH rejection flags at the requested FDR level.
rejectWeightedBenjaminiYekutieli(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns weighted-BY rejection flags.
rejectWeightedBonferroni(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns weighted-Bonferroni rejection flags.
rejectWeightedHolm(double[], double[], double) - Static method in class jdistlib.disttest.MultipleTesting: Returns weighted-Holm rejection flags.
relativeDiff(double[], double[]) - Static method in class jdistlib.math.VectorMath
relativeMcse() - Method in class jdistlib.inference.PrecisionGoal
relativeMcse(double) - Method in class jdistlib.inference.PrecisionGoal.Builder
relativeTolerance - Variable in class jdistlib.inference.solver.OdeSolver.Options
relativeTolerance - Variable in class jdistlib.inference.solver.StiffOdeSolver.Options
relativeTolerance - Variable in class jdistlib.MultivariateProbabilityOptions
reliable() - Method in class jdistlib.inference.LooModelComparison.Entry
reliable() - Method in class jdistlib.inference.McmcDiagnosticReport
reliable() - Method in class jdistlib.inference.ParameterDiagnostics
reliable() - Method in class jdistlib.inference.ParetoSmoothedImportanceSampling.Result
reliable() - Method in class jdistlib.inference.PathfinderFit
reliable() - Method in class jdistlib.inference.PsisLoo.Result: True when all k diagnostics are acceptable or every unacceptable value was replaced.
reliable() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
reliable() - Method in class jdistlib.inference.Waic.Result
remainingArguments() - Method in class jdistlib.inference.InferenceCliOptions
remediation() - Method in class jdistlib.inference.HealthIssue
render(String, McmcDiagnosticReport, ModelGraph, ChartSpec...) - Static method in class jdistlib.inference.InferenceHtmlReport
rep(double[], int) - Static method in class jdistlib.util.Utilities
rep(double, int) - Static method in class jdistlib.util.Utilities
rep_each(double[], int) - Static method in class jdistlib.util.Utilities
rep_each(int[], int) - Static method in class jdistlib.util.Utilities
repeatabilityChecks(int) - Method in class jdistlib.FunctionAnalysisOptions.Builder
repeated(ParameterConstraint, int) - Static method in class jdistlib.inference.Constraints: Repeats an independent constraint transform, as required for arrays of constrained values.
replications - Variable in class jdistlib.MultivariateProbabilityOptions
requested() - Method in class jdistlib.accelerator.ComputeSelection
resampledDraws() - Method in class jdistlib.inference.PathfinderOptions
resampledDraws(int) - Method in class jdistlib.inference.PathfinderOptions.Builder
reset() - Method in class jdistlib.disttest.online.LordPlusPlus
reset() - Method in interface jdistlib.disttest.online.OnlineFdrController: Restores the controller to its newly constructed state.
reset() - Method in class jdistlib.disttest.online.Saffron
reset() - Method in class jdistlib.inference.autodiff.ReverseTape: Clears all nodes while retaining the arena capacity.
reset() - Method in class jdistlib.inference.EvaluationCounter
resetAdaptation() - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
resetAdaptation() - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
resetAdaptation() - Method in class jdistlib.inference.ModelSpecificRjKernel
resetAdaptation() - Method in interface jdistlib.inference.ReversibleJumpMove
resetAdaptation() - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
resetAdaptation() - Method in interface jdistlib.inference.RjBirthProposal
resetAdaptation() - Method in class jdistlib.inference.SubsetBirthMove
resetAdaptation() - Method in class jdistlib.inference.SubsetDeathMove
resetAdaptation() - Method in class jdistlib.inference.SubsetSwapMove
residual(double, double[], double[], double[], double[], double[]) - Method in interface jdistlib.inference.solver.DaeSystem: Writes the DAE residual into residual.
ResidualInformedSparseCandidateProposal - Class in jdistlib.inference: Locally informed candidate proposal using a prepared X'v product.
ResidualInformedSparseCandidateProposal(PreparedTransposeProduct, SparseResidualProvider, double, double) - Constructor for class jdistlib.inference.ResidualInformedSparseCandidateProposal
residualNorm() - Method in class jdistlib.inference.solver.AlgebraicSolver.Result
resolve(int) - Method in class jdistlib.inference.WarmupSchedule: Resolves the requested schedule to a particular warmup length.
restoreAdaptation(Map<String, double[]>) - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
restoreAdaptation(Map<String, double[]>) - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
restoreAdaptation(Map<String, double[]>) - Method in class jdistlib.inference.ModelSpecificRjKernel
restoreAdaptation(Map<String, double[]>) - Method in interface jdistlib.inference.ReversibleJumpMove
restoreAdaptation(Map<String, double[]>) - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
restoreAdaptation(Map<String, double[]>) - Method in interface jdistlib.inference.RjBirthProposal
restoreAdaptation(Map<String, double[]>) - Method in class jdistlib.inference.SubsetBirthMove
restoreAdaptation(Map<String, double[]>) - Method in class jdistlib.inference.SubsetDeathMove
restoreAdaptation(Map<String, double[]>) - Method in class jdistlib.inference.SubsetSwapMove
result - Variable in class jdistlib.math.IntegrationResult
result() - Method in class jdistlib.inference.OptimizationTrace
ResumableSampler - Interface in jdistlib.inference: Sampler capable of restoring algorithm-specific adaptive state.
resume(LogDensity, ChainCheckpoint, SamplingOptions) - Method in class jdistlib.inference.NoUTurnSampler
resume(LogDensity, ChainCheckpoint, SamplingOptions) - Method in interface jdistlib.inference.ResumableSampler
resume(ReversibleJumpTarget, ReversibleJumpCheckpoint, ReversibleJumpSamplingOptions) - Method in class jdistlib.inference.ReversibleJumpSampler
resume(Sampler, LogDensity, ChainCheckpoint, SamplingOptions) - Static method in class jdistlib.inference.Chains: Restarts from the state and cloned stream stored by an in-memory checkpoint.
resume(SparseSubsetTarget, SparseSubsetCheckpoint, SparseSubsetSamplingOptions) - Method in class jdistlib.inference.SparseSubsetRjSampler
retainedDraws() - Method in class jdistlib.inference.SparseSubsetCheckpoint
retainedDraws() - Method in class jdistlib.inference.SparseSubsetSummary
retainedIndices() - Method in class jdistlib.inference.ColumnarDraws
retry(LogDensity, double[], double, int, RandomEngine) - Static method in class jdistlib.inference.InitialStates
RETURN - Enum constant in enum class jdistlib.finance.RiskConvention
returnLevel(double, double, double, double) - Static method in class jdistlib.finance.ExtremeValueInference
reusableSparseFactorizations() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether sparse symbolic analysis is reusable when only numerical values change.
rev(double[]) - Static method in class jdistlib.util.Utilities
reverse(int) - Method in class jdistlib.inference.autodiff.ReverseTape: Runs one reverse sweep with unit seed at output.
ReverseDifferentiableFunction - Interface in jdistlib.inference.autodiff: Builds a scalar expression from parameter handles on a reverse-mode tape.
ReverseModeGradient - Class in jdistlib.inference.autodiff: Reusable reverse-mode value-and-gradient evaluator.
ReverseModeGradient() - Constructor for class jdistlib.inference.autodiff.ReverseModeGradient
ReverseModeGradient(ReverseTape) - Constructor for class jdistlib.inference.autodiff.ReverseModeGradient
ReverseModeLogDensity - Class in jdistlib.inference.autodiff: Reusable reverse-mode log density suitable for HMC and NUTS.
ReverseModeLogDensity(int, ReverseDifferentiableFunction) - Constructor for class jdistlib.inference.autodiff.ReverseModeLogDensity
ReverseModeLogDensity(int, ReverseDifferentiableFunction, int) - Constructor for class jdistlib.inference.autodiff.ReverseModeLogDensity
reverseMove() - Method in class jdistlib.inference.ReversibleJumpProposal
ReverseTape - Class in jdistlib.inference.autodiff: Allocation-conscious reverse-mode automatic-differentiation tape.
ReverseTape() - Constructor for class jdistlib.inference.autodiff.ReverseTape
ReverseTape(int) - Constructor for class jdistlib.inference.autodiff.ReverseTape
ReverseWeibull - Class in jdistlib.evd: Reverse Weibull distribution.
ReverseWeibull(double, double, double) - Constructor for class jdistlib.evd.ReverseWeibull
ReversibleJumpChains - Class in jdistlib.inference: Deterministic parallel execution with one independently adaptive RJ sampler per chain.
ReversibleJumpCheckpoint - Class in jdistlib.inference: Exact in-memory RJ restart point including ragged state, schedule, adaptation, and RNG.
ReversibleJumpCheckpoint(ReversibleJumpState, double, int, RandomEngine, String[], double[], Map<String, double[]>, boolean) - Constructor for class jdistlib.inference.ReversibleJumpCheckpoint
ReversibleJumpCheckpointIO - Class in jdistlib.inference: Checksummed portable persistence for complete reversible-jump restart state.
ReversibleJumpDiagnosticReport - Class in jdistlib.inference: Model occupancy, movement, inclusion, conditional-parameter, and reliability diagnostics.
ReversibleJumpDiagnostics - Class in jdistlib.inference: Multi-chain diagnostics for ragged reversible-jump output.
ReversibleJumpDrawSink - Interface in jdistlib.inference: Streaming sink for ragged retained RJ draws.
ReversibleJumpExport - Class in jdistlib.inference: Tidy CSV export for ragged model-specific parameters.
ReversibleJumpIterationStats - Class in jdistlib.inference: Per-iteration within-model and trans-dimensional transition statistics.
ReversibleJumpIterationStats(long, long, String, boolean, boolean, boolean, double, double, int, int) - Constructor for class jdistlib.inference.ReversibleJumpIterationStats
ReversibleJumpModelSpace - Class in jdistlib.inference: Named parameter schema for one model in a trans-dimensional target.
ReversibleJumpModelSpace(long, String, String...) - Constructor for class jdistlib.inference.ReversibleJumpModelSpace
ReversibleJumpMove - Interface in jdistlib.inference: One dimension-changing or structure-changing reversible proposal.
ReversibleJumpParameterSummary - Class in jdistlib.inference: Posterior summary conditional on a ragged parameter being present.
ReversibleJumpProgressListener - Interface in jdistlib.inference: Progress callback for one trans-dimensional chain.
ReversibleJumpProposal - Class in jdistlib.inference: Transactional RJ proposal including all non-schedule Hastings terms.
ReversibleJumpResult - Class in jdistlib.inference: Immutable ragged RJMCMC draws, transition statistics, diagnostics inputs, and restart state.
ReversibleJumpResult.Status - Enum Class in jdistlib.inference
ReversibleJumpSampler - Class in jdistlib.inference: General Java-only RJMCMC acceptance engine with warmup-frozen move and within-model adaptation.
ReversibleJumpSampler(ReversibleJumpMove[], double[], ReversibleJumpWithinModelKernel...) - Constructor for class jdistlib.inference.ReversibleJumpSampler
ReversibleJumpSamplerFactory - Interface in jdistlib.inference: Creates one independently mutable reversible-jump sampler per chain.
ReversibleJumpSamplingOptions - Class in jdistlib.inference: Warmup, retention, schedule-adaptation, and streaming options for RJMCMC.
ReversibleJumpSamplingOptions.Builder - Class in jdistlib.inference
ReversibleJumpState - Class in jdistlib.inference: Immutable model identifier and its dimension-specific parameter vector.
ReversibleJumpState(long, double...) - Constructor for class jdistlib.inference.ReversibleJumpState
ReversibleJumpTarget - Interface in jdistlib.inference: Complete normalized joint density and schemas across a family of models.
ReversibleJumpWithinModelKernel - Interface in jdistlib.inference: A fixed-model update scheduled between trans-dimensional proposals.
ReversibleJumpWithinModelTransition - Class in jdistlib.inference: Outcome of one within-model transition in an RJ schedule.
ReversibleJumpWithinModelTransition(ReversibleJumpState, double, boolean, double) - Constructor for class jdistlib.inference.ReversibleJumpWithinModelTransition
rewind(int) - Method in class jdistlib.inference.autodiff.ReverseTape: Discards nodes created after mark, retaining their storage.
rexpm1(double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- EVALUATION OF THE FUNCTION EXP(X) - 1 -----------------------------------------------------------------------
rHat() - Method in class jdistlib.inference.ParameterDiagnostics
Rice - Class in jdistlib: Rice (Rician) distribution with scale sigma and distance nu.
Rice(double, double) - Constructor for class jdistlib.Rice
RIGHT - Enum constant in enum class jdistlib.accelerator.MatrixSide
RIGHT_CENSORED - Enum constant in enum class jdistlib.finance.DistributionFit.Observation.Kind
rightCensored(double) - Static method in class jdistlib.finance.DistributionFit.Observation
rightInfinite(UnivariateFunction, long, DiscreteTailBound, CertifiedDiscreteOptions) - Static method in class jdistlib.CertifiedInfiniteDiscreteDistribution: Constructs support start, start+1, ....
rightPowerLaw(double, double) - Static method in class jdistlib.DiscreteTailBounds: Right-tail integral-test bound for weights proportional to (k + offset)^(-exponent).
rightSingularVectorsTransposed() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition: Returns row-major thin V-transpose with shape components by columns.
rightSingularVectorsTransposed() - Method in class jdistlib.accelerator.SingularValueDecomposition: Returns row-major thin V-transpose with shape components by columns.
RISK_NEUTRAL - Enum constant in enum class jdistlib.finance.OptionInference.Measure
RiskConvention - Enum Class in jdistlib.finance: Whether observations are already losses or are returns (loss is minus return).
RjBirthProposal - Interface in jdistlib.inference: Auxiliary-variable proposal used to create a newly active scalar parameter.
rle(double[]) - Static method in class jdistlib.util.Utilities: Compute RLE
rlog1(double) - Static method in class jdistlib.math.MathFunctions: ----------------------------------------------------------------------- Evaluation of the function x - ln(1 + x) -----------------------------------------------------------------------
RotatedCopula - Class in jdistlib: Bivariate 90, 180 (survival), or 270 degree rotation of a copula.
RotatedCopula(Copula, RotatedCopula.Rotation) - Constructor for class jdistlib.RotatedCopula
RotatedCopula.Rotation - Enum Class in jdistlib
round(double, int) - Static method in class jdistlib.math.MathFunctions: Rounding to desired num places
round(float, int) - Static method in class jdistlib.math.MathFunctions
ROUNDOFF - Enum constant in enum class jdistlib.math.IntegrationStatus
roundTrips() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
rows() - Method in class jdistlib.accelerator.FloatPivotedQrFactor
rows() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition
rows() - Method in class jdistlib.accelerator.PivotedQrFactor: Returns the number of rows in the original matrix.
rows() - Method in interface jdistlib.accelerator.PreparedCsrMatrix
rows() - Method in interface jdistlib.accelerator.PreparedDenseMatrix
rows() - Method in interface jdistlib.accelerator.PreparedFloatCsrMatrix
rows() - Method in interface jdistlib.accelerator.PreparedFloatDenseMatrix
rows() - Method in interface jdistlib.accelerator.PreparedLogisticRegression
rows() - Method in interface jdistlib.accelerator.PreparedTransposeProduct
rows() - Method in class jdistlib.accelerator.SingularValueDecomposition
rows() - Method in class jdistlib.inference.AcceleratedLogisticRegression
rows() - Method in class jdistlib.matrix.CsrMatrix
rows() - Method in class jdistlib.matrix.FloatCsrMatrix
rowStarts() - Method in class jdistlib.matrix.CsrMatrix
rowStarts() - Method in class jdistlib.matrix.FloatCsrMatrix
rr - Variable in class jdistlib.Tukey
run(Sampler, LogDensity, double[][], int, SamplingOptions, long, int) - Static method in class jdistlib.inference.ManyShortChains
run(Sampler, LogDensity, double[], SamplingOptions, PrecisionGoal, int, RandomEngine) - Static method in class jdistlib.inference.PrecisionContinuation
run(Sampler, LogDensity, SuperchainPlan, SamplingOptions, long, int) - Static method in class jdistlib.inference.ManyShortChains
RunManifest - Class in jdistlib.inference: Immutable provenance record for reproducing one inference run.
runningMaximum(GenericDistribution, int) - Static method in class jdistlib.finance.PathFunctionalDistributions
runningMinimum(GenericDistribution, int) - Static method in class jdistlib.finance.PathFunctionalDistributions
runtimeCompilation() - Method in class jdistlib.accelerator.ComputeCapabilities

S

s - Variable in class jdistlib.HyperGeometric.RandomState
s - Variable in class jdistlib.Zipf
saddlepointCumulative(TransformDistribution, double) - Static method in class jdistlib.finance.DistributionTransforms: Lugannani-Rice saddlepoint CDF using numerical derivatives of log M(t).
Saffron - Class in jdistlib.disttest.online: Stateful constant-candidate-threshold SAFFRON online-FDR controller.
Saffron(double, double, double, double[]) - Constructor for class jdistlib.disttest.online.Saffron
sample(int) - Method in class jdistlib.inference.ChainResult
sample(int, ReversibleJumpState, RandomEngine) - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
sample(int, ReversibleJumpState, RandomEngine) - Method in class jdistlib.inference.GaussianRjBirthProposal
sample(int, ReversibleJumpState, RandomEngine) - Method in interface jdistlib.inference.RjBirthProposal
sample(int, SparseSubsetState, RandomEngine) - Method in class jdistlib.inference.GaussianSparseCoefficientProposal
sample(int, SparseSubsetState, RandomEngine) - Method in interface jdistlib.inference.SparseCoefficientProposal
sample(long, long, int, long, long[], int, RandomEngine) - Static method in class jdistlib.rng.RandomSampler: Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
sample(DifferentiableLogDensity, double[][], AdaptiveStaticHmcOptions, long) - Static method in class jdistlib.inference.AdaptiveStaticHamiltonianMonteCarlo
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.AdjustedMicrocanonicalLangevin
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.BarkerGradientSampler
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.ComponentWiseMetropolis
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.EllipticalSliceSampler
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.GibbsSampler
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.HamiltonianMonteCarlo
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.HybridSampler
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.MetropolisAdjustedLangevin
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.NoUTurnSampler
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.RandomWalkMetropolis
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in interface jdistlib.inference.Sampler
sample(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.SliceSampler
sample(ReversibleJumpTarget, ReversibleJumpState, ReversibleJumpSamplingOptions, RandomEngine) - Method in class jdistlib.inference.ReversibleJumpSampler
sample(SparseSubsetState, SparseSubsetTarget, RandomEngine) - Method in class jdistlib.inference.ResidualInformedSparseCandidateProposal
sample(SparseSubsetState, SparseSubsetTarget, RandomEngine) - Method in interface jdistlib.inference.SparseCandidateProposal
sample(SparseSubsetState, SparseSubsetTarget, RandomEngine) - Method in class jdistlib.inference.UniformSparseCandidateProposal
sample(SparseSubsetTarget, SparseSubsetState, SparseSubsetSamplingOptions, RandomEngine) - Method in class jdistlib.inference.SparseSubsetRjSampler
sample(TemperedLogDensity, double[], double[], SamplingOptions, RandomEngine) - Static method in class jdistlib.inference.ParallelTempering
sample(RandomEngine) - Method in class jdistlib.AdaptiveRejectionSampler
sample(RandomEngine) - Method in interface jdistlib.RejectionEnvelope: Draws from the normalized proposal distribution.
sample(RandomEngine) - Method in class jdistlib.UniformRejectionEnvelope
sample_int(int, int) - Static method in class jdistlib.util.Utilities: Sample from 1 to n, with size s, without replacement---with default random engine
sample_int(int, int, RandomEngine) - Static method in class jdistlib.util.Utilities: Sample from 1 to n, with size s, without replacement
sampleCount(int) - Method in class jdistlib.FunctionAnalysisOptions.Builder
sampleIterations() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
sampleIterations() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
sampleIterations() - Method in class jdistlib.inference.SamplingOptions
sampleIterations(int) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
sampleIterations(int) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
sampleIterations(int) - Method in class jdistlib.inference.SamplingOptions.Builder
sampleMethodA(long, long, int, long, long[], int, RandomEngine) - Static method in class jdistlib.rng.RandomSampler: Computes a sorted random set of count elements from the interval [low,low+N-1].
sampleMethodD(long, long, int, long, long[], int, RandomEngine) - Static method in class jdistlib.rng.RandomSampler: Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
sampleMixed(LogDensity, double[], SamplingOptions, RandomEngine) - Method in class jdistlib.inference.HybridSampler
sampler() - Method in class jdistlib.inference.McmcDiagnosticReport
sampler() - Method in class jdistlib.inference.RunManifest
sampler() - Method in class jdistlib.inference.SamplerCheckpoint
sampler(RjBirthProposal, double, double) - Static method in class jdistlib.inference.SubsetSelectionRj
Sampler - Interface in jdistlib.inference: Common contract for a reproducible MCMC chain.
samplerCheckpoint() - Method in class jdistlib.inference.ChainCheckpoint
SamplerCheckpoint - Class in jdistlib.inference: Versioned sampler-specific adaptation state for exact resumability.
SamplerCheckpoint(String, int, int, double, double, double[][], double[], int, double[], double[][]) - Constructor for class jdistlib.inference.SamplerCheckpoint
SamplerCheckpoint(String, int, int, double, double, double[][], double[], int, double[], double[][], double) - Constructor for class jdistlib.inference.SamplerCheckpoint
SamplerDiagnostics - Class in jdistlib.inference: Cross-chain sampler health summary.
samples - Variable in class jdistlib.VineProbabilityResult
samples() - Method in class jdistlib.inference.ChainResult
SamplingOptions - Class in jdistlib.inference: Immutable common MCMC warmup, retention, adaptation, and safety options.
SamplingOptions.Builder - Class in jdistlib.inference
SamplingStrategy - Enum Class in jdistlib: Sampling algorithm currently selected by a numerical distribution.
sasum(int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
saxpy(int, float, float[], int, int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
SCAL - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
scalar(double, double...) - Static method in class jdistlib.inference.lang.ExternalFunctionResult
scalar(String) - Method in class jdistlib.inference.ModelData
scalar(String) - Method in class jdistlib.inference.ModelState
scale - Variable in class jdistlib.Cauchy
scale - Variable in class jdistlib.evd.Fretchet
scale - Variable in class jdistlib.evd.GeneralizedPareto
scale - Variable in class jdistlib.evd.GEV
scale - Variable in class jdistlib.evd.Gumbel
scale - Variable in class jdistlib.evd.Rayleigh
scale - Variable in class jdistlib.evd.ReverseWeibull
scale - Variable in class jdistlib.Exponential
scale - Variable in class jdistlib.Gamma
scale - Variable in class jdistlib.InvGamma
scale - Variable in class jdistlib.Laplace
scale - Variable in class jdistlib.Logistic
scale - Variable in class jdistlib.LogLogistic
scale - Variable in class jdistlib.Weibull
scale(long) - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
scalefactor - Static variable in class jdistlib.math.MathFunctions
scaleUpdates() - Method in class jdistlib.inference.SparseSubsetCheckpoint
SCATTER - Enum constant in enum class jdistlib.inference.ChartSpec.Type
scenario(GenericDistribution, DistributionAggregation.ScenarioTransformation, int, long) - Static method in class jdistlib.finance.DistributionAggregation: Applies caller-supplied scenarios to a base law with explicit seed provenance.
scopy(int, float[], int, int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
scores() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
scoreVector(SparseSubsetState) - Method in interface jdistlib.inference.SparseResidualProvider
ScriptDiagnostic - Class in jdistlib.inference.lang: Source-located modeling-language diagnostic.
ScriptDiagnostic(int, int, String) - Constructor for class jdistlib.inference.lang.ScriptDiagnostic
scsrgemm(FloatCsrMatrix, FloatCsrMatrix) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
scsrmm(float, FloatCsrMatrix, float[], int, float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
scsrmv(float, FloatCsrMatrix, float[], float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
scsrpotrf(FloatCsrMatrix, MatrixTriangle) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
scsrpotrf(FloatCsrMatrix, MatrixTriangle, SparseOrdering) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
scsrsv(MatrixTriangle, MatrixTranspose, MatrixDiagonal, FloatCsrMatrix, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sd(double[]) - Static method in class jdistlib.math.VectorMath
sdlog - Variable in class jdistlib.LogNormal
sdot(int, float[], int, int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
seed() - Method in class jdistlib.inference.RunManifest
segmentTransitions() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
segmentTransitions(int) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
select(double[][]) - Static method in class jdistlib.CopulaSelector
select(double[][], String[], double[][], double[], double[], double) - Static method in class jdistlib.inference.ProjectionPredictiveSelection
select(double[][], CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.CopulaSelector
select(Compute) - Static method in class jdistlib.accelerator.ComputeBackends: Selects and reports an owned backend according to the requested policy.
selected() - Method in class jdistlib.inference.ShrinkageSelection.Result
selected() - Method in class jdistlib.inference.ShrinkageSelection.Variable
selectedBackend() - Method in interface jdistlib.accelerator.ComputeBackend: Concrete provider used for accelerated work; differs from ComputeBackend.id() for AUTO routing.
selectedBackend() - Method in class jdistlib.accelerator.ComputeSelection: Returns the concrete provider used for accelerated work, or cpu.
selectedElbos() - Method in class jdistlib.inference.PathfinderFit
selectedModel() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Result
selectedPathIterations() - Method in class jdistlib.inference.PathfinderFit
selectiveGroupedBenjaminiHochberg(double[], int[], double, double) - Static method in class jdistlib.disttest.MultipleTesting: Selects groups with BH on Simes p-values and tests selected groups with selection-adjusted BH.
selectMixed(double[][], CopulaMarginal[], long, CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.CopulaSelector: Selects a family after a reproducible randomized marginal transform.
selectMixed(double[][], CopulaMarginal[], CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.CopulaSelector: Selects a family after continuous/discrete marginal transformation.
selectMixed(double[][], CopulaMarginal[], RandomEngine, CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.CopulaSelector: Selects a family after continuous/discrete marginal transformation.
selectUniforms(double[][], CopulaFitOptions, CopulaSelectionCriterion, CopulaFamily...) - Static method in class jdistlib.CopulaSelector
sensitivities() - Method in class jdistlib.inference.solver.SensitivityResult: Derivatives indexed by output point, state component, then parameter.
SensitivityResult - Class in jdistlib.inference.solver: Values and first-order parameter sensitivities returned by a numerical solver.
seq(double, double, double) - Static method in class jdistlib.util.Utilities
seq(int, int, int) - Static method in class jdistlib.util.Utilities
seq_along(double[]) - Static method in class jdistlib.util.Utilities
seq_int(double, double, int) - Static method in class jdistlib.util.Utilities
series() - Method in class jdistlib.inference.ChartSpec
Series(String, double[], double[]) - Constructor for class jdistlib.inference.ChartSpec.Series
setCoefficient(int, double) - Method in class jdistlib.math.Polynomial: Set coefficient of this polynomial
setInitialGuess(double[]) - Method in class jdistlib.math.opt.OptimizationConfig
setInitialTrustRegionRadius(double) - Method in class jdistlib.math.opt.BobyqaConfig
setLower(double) - Method in class jdistlib.math.density.Bandwidth
setLowerBound(double[]) - Method in class jdistlib.math.opt.OptimizationConfig
setMaxNumFunctionCall(int) - Method in class jdistlib.math.opt.OptimizationConfig
setMinimize(boolean) - Method in class jdistlib.math.opt.OptimizationConfig
setNumBins(int) - Method in class jdistlib.math.density.Bandwidth
setNumInterpolationPoints(int) - Method in class jdistlib.math.opt.BobyqaConfig
setObjectiveFunction(MultivariableFunction) - Method in class jdistlib.math.opt.OptimizationConfig
setObjects(Object...) - Method in class jdistlib.math.approx.ApproximationFunction
setObjects(Object...) - Method in interface jdistlib.math.UnivariateFunction
setParameters(double...) - Method in class jdistlib.math.approx.ApproximationFunction
setParameters(double...) - Method in interface jdistlib.math.UnivariateFunction
setRandomEngine(RandomEngine) - Method in class jdistlib.generic.GenericDistribution
setRandomEngine(RandomEngine) - Method in class jdistlib.SignRank
setSeed(int[]) - Method in class jdistlib.rng.MersenneTwister: Sets the seed of the MersenneTwister using an array of integers.
setSeed(int[]) - Method in class jdistlib.rng.MersenneTwisterSafe: Sets the seed of the MersenneTwister using an array of integers.
setSeed(long) - Method in class jdistlib.rng.MersenneTwister: Initalize the pseudo random number generator.
setSeed(long) - Method in class jdistlib.rng.MersenneTwisterSafe: Initalize the pseudo random number generator.
setSeed(long) - Method in class jdistlib.rng.RandomEngine
setSeed(long) - Method in class jdistlib.rng.RandomWELL44497b
setStoppingTrustRegionRadius(double) - Method in class jdistlib.math.opt.BobyqaConfig
setTolerance(double) - Method in class jdistlib.math.density.Bandwidth
setUpper(double) - Method in class jdistlib.math.density.Bandwidth
setUpperBound(double[]) - Method in class jdistlib.math.opt.OptimizationConfig
setValue(double) - Method in exception class jdistlib.exception.PrecisionException
severity() - Method in class jdistlib.inference.HealthIssue
sgemm(MatrixTranspose, MatrixTranspose, int, int, int, float, float[], float[], float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sgemm(MatrixTranspose, MatrixTranspose, int, int, int, float, float[], int, int, float[], int, int, float, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend: Region-aware GEMM with row-major offsets and leading dimensions.
sgemmBatched(MatrixTranspose, MatrixTranspose, int, int, int, float, float[][], float[][], float, float[][]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sgemv(MatrixTranspose, int, int, float, float[], float[], float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sgemv(MatrixTranspose, int, int, float, float[], int, int, float[], int, int, float, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend: Region-aware GEMV with a row-major leading dimension and strided vectors.
sgeqp3(float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sger(int, int, float, float[], int, int, float[], int, int, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sgesvd(float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sgetrf(float[], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sgetrfBatched(float[][], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
shape - Variable in class jdistlib.evd.Fretchet
shape - Variable in class jdistlib.evd.GeneralizedPareto
shape - Variable in class jdistlib.evd.GEV
shape - Variable in class jdistlib.evd.ReverseWeibull
shape - Variable in class jdistlib.Gamma
shape - Variable in class jdistlib.InvGamma
shape - Variable in class jdistlib.LogLogistic
shape - Variable in class jdistlib.Weibull
shape() - Method in class jdistlib.inference.lang.ExternalFunctionResult
shapiro_francia_pvalue(double, int) - Static method in class jdistlib.disttest.NormalityTest: P-value of Shapiro-Francia normality test
shapiro_francia_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest: Shapiro-Francia normality test
shapiro_wilk_pvalue(double, int) - Static method in class jdistlib.disttest.NormalityTest
shapiro_wilk_statistic(double[]) - Static method in class jdistlib.disttest.NormalityTest: Invoke shapiro_wilk_statistic with sort = false
shapiro_wilk_statistic(double[], boolean) - Static method in class jdistlib.disttest.NormalityTest: Compute Shapiro-Wilk statistic
shortfallProbability(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk
ShrinkageSelection - Class in jdistlib.inference: Ranks posterior coefficient draws by practical-significance probability.
ShrinkageSelection.Result - Class in jdistlib.inference
ShrinkageSelection.Variable - Class in jdistlib.inference
SIDAK - Enum constant in enum class jdistlib.disttest.MultipleTesting.Method: Single-step Sidak control for independent tests.
sigma - Variable in class jdistlib.BetaBinomial
sigma - Variable in class jdistlib.InvNormal
sigma - Variable in class jdistlib.Levy
sigma - Variable in class jdistlib.Normal
sigma - Variable in class jdistlib.Wilcoxon
signif(double, int) - Static method in class jdistlib.math.MathFunctions: Mimicking R's signif
SignRank - Class in jdistlib
SignRank(int) - Constructor for class jdistlib.SignRank
simplex(int) - Static method in class jdistlib.inference.Constraints
simplify() - Method in class jdistlib.math.Polynomial: Can we simplify this polynomial? If the lowest coefficients are zero, the polynomial looks like x^n * simpler_polynomial.
SimulationBasedCalibration - Class in jdistlib.inference: Seeded simulation-based calibration rank utility.
SimulationBasedCalibration.Generator - Interface in jdistlib.inference
SimulationBasedCalibration.Simulation - Interface in jdistlib.inference
sin() - Method in class jdistlib.math.Complex
sin(int) - Method in class jdistlib.inference.autodiff.ReverseTape
sinc(double) - Static method in class jdistlib.math.MathFunctions: Compute sinc(x) = sin(x)/x for x != 0.
SinglePrecisionLinearAlgebraBackend - Interface in jdistlib.accelerator: Backend-neutral FP32 BLAS, sparse-BLAS, and reusable factorization surface.
singularities(double...) - Method in class jdistlib.NumericalContinuousDistribution.Builder
singularity(double) - Method in class jdistlib.NumericalSupport.Builder: Declares a finite split point for integration.
SingularValueDecomposition - Class in jdistlib.accelerator: Immutable FP64 thin singular-value decomposition A = U*S*Vt.
SingularValueDecomposition(int, int, double[], double[], double[]) - Constructor for class jdistlib.accelerator.SingularValueDecomposition: Creates a thin SVD with descending singular values.
singularValues() - Method in class jdistlib.accelerator.FloatSingularValueDecomposition: Returns singular values in descending order.
singularValues() - Method in class jdistlib.accelerator.SingularValueDecomposition: Returns singular values in descending order.
sinh() - Method in class jdistlib.math.Complex
SinhArcsinh - Class in jdistlib: Four-parameter sinh-arcsinh distribution of Jones and Pewsey.
SinhArcsinh(double, double, double, double) - Constructor for class jdistlib.SinhArcsinh
sinpi(double) - Static method in class jdistlib.math.MathFunctions
size - Variable in class jdistlib.NegBinomial
size() - Method in class jdistlib.finance.EmpiricalDistribution
size() - Method in class jdistlib.inference.autodiff.ReverseTape: Current node count, useful for instrumentation and capacity planning.
size() - Method in class jdistlib.inference.ChainResult
size() - Method in class jdistlib.inference.ChartSpec.Series
size() - Method in class jdistlib.inference.ColumnarDraws
size() - Method in class jdistlib.inference.lang.TupleValue
size() - Method in class jdistlib.inference.ModelData
size() - Method in class jdistlib.inference.ObservationMetadata
size() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Step
size() - Method in class jdistlib.inference.ReversibleJumpResult
size() - Method in class jdistlib.inference.SparseSubsetResult
size() - Method in class jdistlib.inference.SparseSubsetState
size() - Method in class jdistlib.NumericalCdfTable
SJ(double[], int, double, double, double, boolean) - Static method in class jdistlib.math.density.Bandwidth
SJ_DPI - Static variable in class jdistlib.math.density.Bandwidth
SJ_STE - Static variable in class jdistlib.math.density.Bandwidth
Skellam - Class in jdistlib: Difference of two independent Poisson variates.
Skellam(double, double) - Constructor for class jdistlib.Skellam
SkewedT - Class in jdistlib: Skewed T distribution, from skewt package
SkewedT(double, double) - Constructor for class jdistlib.SkewedT
Slash - Class in jdistlib: Location-scale slash distribution, mu + sigma * Z / U.
Slash(double, double) - Constructor for class jdistlib.Slash
SliceSampler - Class in jdistlib.inference: Coordinate-wise stepping-out and shrinkage slice sampler.
SliceSampler() - Constructor for class jdistlib.inference.SliceSampler
sliceWidth() - Method in class jdistlib.inference.SamplingOptions
sliceWidth(double) - Method in class jdistlib.inference.SamplingOptions.Builder
SLOW - Enum constant in enum class jdistlib.inference.WarmupSchedule.Phase
slowWindowEnds() - Method in class jdistlib.inference.WarmupSchedule.Resolved
smooth(double[]) - Static method in class jdistlib.inference.ParetoSmoothedImportanceSampling
smoothDistribution(double) - Method in class jdistlib.finance.OptionCurve: Optional smooth nonnegative density with quote and bandwidth-sensitivity diagnostics.
SmoothOptionDistributionResult - Class in jdistlib.finance: Smooth risk-neutral density plus regularization and differentiation diagnostics.
SmoothSpline - Class in jdistlib.math.spline: This class deals with smoothing of cubic B-Splines.
SmoothSpline() - Constructor for class jdistlib.math.spline.SmoothSpline
SmoothSplineCriterion - Enum Class in jdistlib.math.spline: Smooth spline criterion.
NO_CRITERION = No additional minimizing criterion
GCV = Generalized Cross Validation
CV = Cross Validation
DF_MATCH = Degree of freedom matching
SmoothSplineResult - Class in jdistlib.math.spline
SmoothSplineResult() - Constructor for class jdistlib.math.spline.SmoothSplineResult
SNAPER - Enum constant in enum class jdistlib.inference.AdaptiveStaticHmcOptions.Criterion
snrm2(int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
solution() - Method in class jdistlib.inference.solver.AlgebraicSolver.Result
solve(double[]) - Method in class jdistlib.accelerator.CholeskyFactor: Solves A*x=right.
solve(double[]) - Method in class jdistlib.accelerator.LuFactor
solve(double[]) - Method in interface jdistlib.accelerator.PreparedSparseCholesky
solve(double[]) - Method in class jdistlib.accelerator.SparseCholeskyFactor: Solves A*x=right in original input coordinates.
solve(double[]) - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
solve(double[], int) - Method in class jdistlib.accelerator.CholeskyFactor: Solves A*X=right for a row-major matrix with the given column count.
solve(double[], int) - Method in class jdistlib.accelerator.LuFactor: Solves A*X=right; right sides use row-major dimension-by-columns storage.
solve(double[], int) - Method in interface jdistlib.accelerator.PreparedSparseCholesky
solve(double[], int) - Method in class jdistlib.accelerator.SparseCholeskyFactor: Solves a row-major dimension-by-columns right side in original coordinates.
solve(double[], int) - Method in class jdistlib.accelerator.SymmetricIndefiniteFactor
solve(float[]) - Method in class jdistlib.accelerator.FloatCholeskyFactor
solve(float[]) - Method in class jdistlib.accelerator.FloatLuFactor
solve(float[]) - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
solve(float[]) - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
solve(float[]) - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
solve(float[], int) - Method in class jdistlib.accelerator.FloatCholeskyFactor: Solves one or more row-major right-hand-side columns.
solve(float[], int) - Method in class jdistlib.accelerator.FloatLuFactor
solve(float[], int) - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
solve(float[], int) - Method in class jdistlib.accelerator.FloatSymmetricIndefiniteFactor
solve(float[], int) - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
solve(AlgebraicSystem, double[], double[], double[], AlgebraicSolver.Options) - Static method in class jdistlib.inference.solver.AlgebraicSolver: Solves from initial; the caller's arrays are never modified.
solveInPlace(double[], int) - Method in interface jdistlib.accelerator.PreparedCholesky: Replaces a row-major dimension-by-columns right side with its solution.
solveInPlace(double[], int) - Method in interface jdistlib.accelerator.PreparedSparseCholesky: Replaces a row-major dimension-by-columns right side with its solution.
solveInPlace(double[], int) - Method in class jdistlib.accelerator.SparseCholeskyFactor: Replaces a row-major dimension-by-columns right side with its solution.
solveInPlace(float[], int) - Method in class jdistlib.accelerator.FloatSparseCholeskyFactor
solveInPlace(float[], int) - Method in interface jdistlib.accelerator.PreparedFloatCholesky: Replaces a row-major dimension-by-columns right side with its solution.
solveInPlace(float[], int) - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
solveLeastSquares(double[]) - Method in class jdistlib.accelerator.PivotedQrFactor: Solves a full-column-rank least-squares problem and returns coefficients in original order.
solveLeastSquares(float[]) - Method in class jdistlib.accelerator.FloatPivotedQrFactor
solveWithSensitivities(AlgebraicSystem, double[], double[], double[], AlgebraicSolver.Options) - Static method in class jdistlib.inference.solver.AlgebraicSolver: Solves the system and differentiates the root with respect to parameters using the implicit-function identity dx/dp = -Jx^-1 Jp.
sort(double[]) - Static method in class jdistlib.util.Utilities: Sort data using radix sort
sort(double[], int[]) - Static method in class jdistlib.util.Utilities: Sort using radix sort
sort(double[], T[]) - Static method in class jdistlib.util.Utilities: Sort using radix sort
sort(int[]) - Static method in class jdistlib.util.Utilities: Radix sort
sort(int[], int[]) - Static method in class jdistlib.util.Utilities
sort(int[], T[]) - Static method in class jdistlib.util.Utilities
sort(long[]) - Static method in class jdistlib.util.Utilities: Radix sort
sort(long[], int[]) - Static method in class jdistlib.util.Utilities
sort(long[], T[]) - Static method in class jdistlib.util.Utilities
sourceHash() - Method in interface jdistlib.inference.lang.GeneratedModelFactory
SparseCandidateChoice - Class in jdistlib.inference: Candidate selected by a normalized sparse birth proposal.
SparseCandidateChoice(int, double) - Constructor for class jdistlib.inference.SparseCandidateChoice
SparseCandidateProposal - Interface in jdistlib.inference: Normalized proposal over candidates inactive in the conditioning model.
SparseCholeskyFactor - Class in jdistlib.accelerator: Immutable FP64 sparse Cholesky factor with reusable solves.
SparseCoefficientProposal - Interface in jdistlib.inference: Dimension-matching proposal for a coefficient born into a sparse model.
sparseLinearAlgebra() - Method in class jdistlib.accelerator.ComputeCapabilities: Whether the provider accelerates the public CSR operations.
SparseOrdering - Enum Class in jdistlib.accelerator: Fill-reducing ordering used before a sparse symmetric factorization.
SparseResidualProvider - Interface in jdistlib.inference: Supplies the row score vector used by a locally informed sparse proposal.
SparseSubsetCheckpoint - Class in jdistlib.inference: Exact sparse RJ restart state, adaptation, counters, RNG, and online summaries.
SparseSubsetCheckpoint(SparseSubsetState, double, long, long, RandomEngine, String[], double[], double[], long[], long[], long[], long[], long[], long[], long[], double[], double[], double[], double[], long, boolean) - Constructor for class jdistlib.inference.SparseSubsetCheckpoint
SparseSubsetCheckpointIO - Class in jdistlib.inference: Checksummed, forced, atomic persistence for complete sparse RJ restart state.
SparseSubsetDrawSink - Interface in jdistlib.inference: Streaming callback for retained sparse draws.
SparseSubsetExport - Class in jdistlib.inference: Crash-safe segment export for ragged sparse draws.
SparseSubsetIterationStats - Class in jdistlib.inference: Per-transition statistics for sparse subset RJMCMC.
SparseSubsetIterationStats(int, int, String, boolean, boolean, boolean, double, double) - Constructor for class jdistlib.inference.SparseSubsetIterationStats
SparseSubsetLogJoint - Interface in jdistlib.inference: Complete normalized log joint for an arbitrary sparse candidate universe.
SparseSubsetProgressListener - Interface in jdistlib.inference: Progress callback for one restartable sparse RJMCMC segment.
SparseSubsetResult - Class in jdistlib.inference: One bounded sparse RJ segment plus its exact continuation checkpoint.
SparseSubsetResult.Status - Enum Class in jdistlib.inference
SparseSubsetRjSampler - Class in jdistlib.inference: Allocation-conscious add/drop/swap RJMCMC for very large sparse candidate universes.
SparseSubsetRjSampler(SparseCandidateProposal, SparseCoefficientProposal, double, double) - Constructor for class jdistlib.inference.SparseSubsetRjSampler
SparseSubsetRjSampler(SparseCandidateProposal, SparseCoefficientProposal, double, double, double[]) - Constructor for class jdistlib.inference.SparseSubsetRjSampler
SparseSubsetSamplingOptions - Class in jdistlib.inference: Global warmup target and bounded transition segment for restartable sparse RJMCMC.
SparseSubsetSamplingOptions.Builder - Class in jdistlib.inference
SparseSubsetState - Class in jdistlib.inference: Immutable sparse subset, common parameters, and active coefficients.
SparseSubsetState(int[], double[], double[]) - Constructor for class jdistlib.inference.SparseSubsetState
SparseSubsetSummary - Class in jdistlib.inference: Online occupancy and conditional-coefficient summary stored in a sparse checkpoint.
SparseSubsetSummary(SparseSubsetTarget, SparseSubsetCheckpoint) - Constructor for class jdistlib.inference.SparseSubsetSummary
SparseSubsetTarget - Class in jdistlib.inference: Sparse subset target with an arbitrary candidate count and a bounded active set.
SparseSubsetTarget(String[], String[], int, SparseSubsetLogJoint) - Constructor for class jdistlib.inference.SparseSubsetTarget
Spearman - Class in jdistlib
Spearman(int) - Constructor for class jdistlib.Spearman
spectral(GenericDistribution, RiskConvention, AdvancedRiskMeasures.SpectralWeight) - Static method in class jdistlib.finance.AdvancedRiskMeasures
splitPoint(double) - Method in class jdistlib.MomentAnalysisOptions.Builder
spotrf(float[], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
spotrfBatched(float[][], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sqrt() - Method in class jdistlib.math.Complex
sqrt(int) - Method in class jdistlib.inference.autodiff.ReverseTape
SQRT - Enum constant in enum class jdistlib.accelerator.UnaryOperation
SQRT_DBL_EPSILON - Static variable in class jdistlib.math.Constants
sscal(int, float, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
sswap(int, float[], int, int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssyev(float[], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssygvd(float[], float[], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssymm(MatrixSide, MatrixTriangle, int, int, float, float[], float[], float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssyr(MatrixTriangle, int, float, float[], int, int, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssyr2(MatrixTriangle, int, float, float[], int, int, float[], int, int, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssyr2k(MatrixTriangle, MatrixTranspose, int, int, float, float[], float[], float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssyrk(MatrixTranspose, int, int, float, float[], float, float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssyrk(MatrixTranspose, int, int, float, float[], int, int, float, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
ssytrf(float[], int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
stable(double, double[], double[][]) - Static method in class jdistlib.finance.MultivariateFinancialDistribution: Symmetric elliptical alpha-stable law with CF exp(-(t' covariance t)^(alpha/2)).
StableDistribution - Class in jdistlib.finance: Univariate alpha-stable law in Nolan's S1 parameterization.
StableDistribution(double, double, double, double) - Constructor for class jdistlib.finance.StableDistribution
stage() - Method in class jdistlib.inference.WarmupTrace.Entry
STAN_SOURCE_COMPATIBILITY - Static variable in class jdistlib.inference.lang.ModelScript
STANDARD - Enum constant in enum class jdistlib.DiagnosticPreset
standardDeviation() - Method in class jdistlib.inference.ParameterDiagnostics
standardDeviation() - Method in class jdistlib.inference.ReversibleJumpParameterSummary
standardDeviation(int) - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
standardDeviation(ModelState, OptionObservation) - Method in interface jdistlib.finance.OptionInference.StateNoiseModel
standardDeviationMcse(double[]) - Static method in class jdistlib.inference.MonteCarloError
standardError - Variable in class jdistlib.VineProbabilityResult
standardError() - Method in class jdistlib.inference.PsisLoo.Result
standardError() - Method in class jdistlib.inference.Waic.Result
standardize(double[]) - Static method in class jdistlib.math.VectorMath: Standardize the value in x (i.e., (x - mean(x)) / sd(x))
standardizedSeparation() - Method in class jdistlib.inference.GeometryAdvice
standardizedTraceCumulative(double, double, double[][], boolean, boolean) - Static method in class jdistlib.Wishart: CDF of trace(scale^-1 W).
stanDefault() - Static method in class jdistlib.inference.WarmupSchedule
StanExternalFunction - Interface in jdistlib.inference.lang: Java implementation of a forward-declared Stan function.
startedEpochMillis() - Method in class jdistlib.inference.RunManifest
state - Variable in class jdistlib.Binomial
state - Variable in class jdistlib.HyperGeometric
state - Variable in class jdistlib.Poisson
state() - Method in class jdistlib.inference.ChainCheckpoint
state() - Method in class jdistlib.inference.DimensionMatchingResult
state() - Method in class jdistlib.inference.KernelTransition
state() - Method in class jdistlib.inference.ModelEvaluationCache
state() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
state() - Method in class jdistlib.inference.ReversibleJumpWithinModelTransition
state() - Method in class jdistlib.inference.SparseSubsetCheckpoint
state(double[]) - Method in class jdistlib.inference.BayesianModel: Returns a named constrained view backed by a fresh transformed state.
state(double[]) - Method in class jdistlib.inference.SparseSubsetTarget
state(int[], double[], double[]) - Method in class jdistlib.inference.SparseSubsetTarget
state(long, double[], double[]) - Method in class jdistlib.inference.SubsetSelectionTarget
stateEquals(MersenneTwister) - Method in class jdistlib.rng.MersenneTwister: Returns true if the MersenneTwister's current internal state is equal to another MersenneTwister.
stateEquals(MersenneTwisterSafe) - Method in class jdistlib.rng.MersenneTwisterSafe: Returns true if the MersenneTwister's current internal state is equal to another MersenneTwister.
statistics() - Method in class jdistlib.inference.ChainResult
statistics() - Method in class jdistlib.inference.KernelTransition
statistics() - Method in class jdistlib.inference.ReversibleJumpResult
statistics() - Method in class jdistlib.inference.SparseSubsetResult
statisticsAt(int) - Method in class jdistlib.inference.ChainResult: Returns immutable statistics for one retained transition.
statisticsAt(int) - Method in class jdistlib.inference.ReversibleJumpResult
statisticsAt(int) - Method in class jdistlib.inference.SparseSubsetResult
status - Variable in class jdistlib.MultivariateProbabilityResult: Stable legacy status code.
status() - Method in class jdistlib.inference.ChainResult
status() - Method in class jdistlib.inference.ReversibleJumpResult
status() - Method in class jdistlib.inference.SparseSubsetResult
step(LogDensity, RandomWalkKernel.State, SamplingOptions, RandomEngine) - Method in class jdistlib.inference.RandomWalkKernel
step(LogDensity, S, SamplingOptions, RandomEngine) - Method in interface jdistlib.inference.TransitionKernel
stepSize() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
stepSize() - Method in class jdistlib.inference.AdaptiveStaticHmcResult
stepSize() - Method in class jdistlib.inference.AdjustedMclmcTuningResult
stepSize() - Method in class jdistlib.inference.IterationStats
stepSize() - Method in class jdistlib.inference.SamplerCheckpoint
stepSize() - Method in class jdistlib.inference.SamplingOptions
stepSize() - Method in class jdistlib.inference.WarmupBundle
stepSize() - Method in class jdistlib.inference.WarmupTrace.Entry
stepSize(double) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
stepSize(double) - Method in class jdistlib.inference.SamplingOptions.Builder
stepSizeJitter() - Method in class jdistlib.inference.SamplingOptions
stepSizeJitter(double) - Method in class jdistlib.inference.SamplingOptions.Builder
StiffOdeSolver - Class in jdistlib.inference.solver: Adaptive A-stable BDF1 integrator for stiff first-order ODE systems.
StiffOdeSolver.Options - Class in jdistlib.inference.solver: Stiff integration controls.
stirlerr(double) - Static method in class jdistlib.math.MathFunctions
stopLoss(GenericDistribution, double) - Static method in class jdistlib.finance.FinancialRisk
stoppingTrustRegionRadius - Variable in class jdistlib.math.opt.BobyqaConfig
storeDraws() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
storeDraws() - Method in class jdistlib.inference.SamplingOptions
storeDraws() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
storeDraws(boolean) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
storeDraws(boolean) - Method in class jdistlib.inference.SamplingOptions.Builder
storeDraws(boolean) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
stressProbability(Copula, Tail, double, Tail, double) - Static method in class jdistlib.finance.CopulaTailAnalysis
STRICT - Enum constant in enum class jdistlib.ConstructionPolicy: Any warning or error prevents construction.
strikeIntervalProbability(double, double) - Method in class jdistlib.finance.OptionCurve
strsm(MatrixSide, MatrixTriangle, MatrixTranspose, MatrixDiagonal, int, int, float, float[], float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
strsm(MatrixSide, MatrixTriangle, MatrixTranspose, MatrixDiagonal, int, int, float, float[], int, int, float[], int, int) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend: Region-aware triangular multi-right-side solve.
strsv(MatrixTriangle, MatrixTranspose, MatrixDiagonal, int, float[], float[]) - Method in interface jdistlib.accelerator.SinglePrecisionLinearAlgebraBackend
structuralNonzeroCount() - Method in interface jdistlib.accelerator.PreparedFloatSparseCholesky
structuralNonzeroCount() - Method in interface jdistlib.accelerator.PreparedSparseCholesky: Number of unique entries in the authoritative input triangle.
STUDENT_T - Enum constant in enum class jdistlib.CopulaFamily
StudentTCopula - Class in jdistlib: Student-t copula parameterized by correlation and degrees of freedom.
StudentTCopula(double[][], double) - Constructor for class jdistlib.StudentTCopula
subdivisions(int) - Method in class jdistlib.math.IntegrationOptions.Builder
SubsetBirthMove - Class in jdistlib.inference: Adds one uniformly selected inactive candidate using a declared birth proposal.
SubsetBirthMove(RjBirthProposal) - Constructor for class jdistlib.inference.SubsetBirthMove
SubsetDeathMove - Class in jdistlib.inference: Drops one uniformly selected active candidate with the matching reverse birth density.
SubsetDeathMove(RjBirthProposal) - Constructor for class jdistlib.inference.SubsetDeathMove
SubsetLogJoint - Interface in jdistlib.inference: Complete normalized log joint for one active-variable subset.
SubsetSelectionRj - Class in jdistlib.inference: Factory for the standard add/drop/swap subset-selection RJ schedule.
SubsetSelectionTarget - Class in jdistlib.inference: Bit-mask model family for Java-only covariate, locus, or feature selection.
SubsetSelectionTarget(String[], String[], SubsetLogJoint) - Constructor for class jdistlib.inference.SubsetSelectionTarget
SubsetSwapMove - Class in jdistlib.inference: Exchanges one active and inactive candidate while preserving model dimension.
SubsetSwapMove(RjBirthProposal) - Constructor for class jdistlib.inference.SubsetSwapMove
subtract(double, int) - Method in class jdistlib.inference.autodiff.ReverseTape
subtract(int, int) - Method in class jdistlib.inference.autodiff.ReverseTape
subtract(Complex) - Method in class jdistlib.math.Complex
SUCCESS - Enum constant in enum class jdistlib.CopulaFitResult.Status
SUCCESS - Enum constant in enum class jdistlib.CopulaLikelihoodDiagnostics.Status
SUCCESS - Enum constant in enum class jdistlib.CopulaLogLikelihoodResult.Status
SUCCESS - Enum constant in enum class jdistlib.inference.ChainResult.Status
SUCCESS - Enum constant in enum class jdistlib.inference.ReversibleJumpResult.Status
SUCCESS - Enum constant in enum class jdistlib.inference.SparseSubsetResult.Status
SUCCESS - Enum constant in enum class jdistlib.math.IntegrationStatus
SUCCESS - Enum constant in enum class jdistlib.MultivariateProbabilityStatus: The requested tolerance was met, or the answer was obtained exactly.
SUCCESS - Enum constant in enum class jdistlib.VineFitResult.Status
SUCCESS - Static variable in class jdistlib.MultivariateProbabilityResult: Legacy integer code corresponding to MultivariateProbabilityStatus.SUCCESS.
suggestion() - Method in class jdistlib.inference.GeometryAdvice
sum(double[]) - Static method in class jdistlib.math.VectorMath
sum(int[]) - Static method in class jdistlib.math.VectorMath
sum(Map<String, Integer>) - Static method in class jdistlib.math.VectorMath
sum_kahan(double[]) - Static method in class jdistlib.math.VectorMath
summary(double[]) - Static method in class jdistlib.math.VectorMath: Return summary statistics
sumToZero(int) - Static method in class jdistlib.inference.Constraints
superchainIds() - Method in class jdistlib.inference.ManyShortChainsResult
SuperchainPlan - Class in jdistlib.inference: Common-start grouping required to interpret nested R-hat.
SuperchainPlan(double[][], int) - Constructor for class jdistlib.inference.SuperchainPlan
superchains() - Method in class jdistlib.inference.SuperchainPlan
supplied(double[][]) - Static method in class jdistlib.inference.MetricConfiguration: Dense, caller-supplied inverse mass matrix; disable adaptation to keep it fixed.
support(double...) - Method in class jdistlib.NumericalDiscreteDistribution.Builder
support(double, double) - Method in class jdistlib.NumericalContinuousDistribution.Builder
support(int) - Method in class jdistlib.inference.MixedStateSpace
support(NumericalSupport) - Method in class jdistlib.NumericalPiecewiseDistribution.Builder
SupportedDistribution - Interface in jdistlib: Distribution object exposing its smallest enclosing support interval.
supportRejected() - Method in class jdistlib.inference.HybridKernelTransition
supportRejections(int) - Method in class jdistlib.inference.HybridSamplerDiagnostics
supports() - Method in class jdistlib.inference.MixedStateSpace
survival(double[]) - Method in class jdistlib.generic.GenericDistribution: Survival function, which is basically 1-CDF.
survival(double[], boolean) - Method in class jdistlib.generic.GenericDistribution
survival(double, boolean) - Method in class jdistlib.generic.GenericDistribution: Survival function, which is basically 1-CDF.
SURVIVAL_180 - Enum constant in enum class jdistlib.RotatedCopula.Rotation
SWAP - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
swapAcceptance(int) - Method in class jdistlib.inference.ParallelTemperingResult
SYEV - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SYGVD - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SYMM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SymmetricEigenDecomposition - Class in jdistlib.accelerator: Immutable FP64 eigendecomposition of a real symmetric matrix.
SymmetricEigenDecomposition(int, double[], double[]) - Constructor for class jdistlib.accelerator.SymmetricEigenDecomposition: Creates a decomposition with ascending eigenvalues and eigenvectors in columns.
SymmetricIndefiniteFactor - Class in jdistlib.accelerator: Immutable pivoted P*A*P' = L*D*L' factorization with 1x1/2x2 D blocks.
SymmetricIndefiniteFactor(int, double[], double[], int[], int[]) - Constructor for class jdistlib.accelerator.SymmetricIndefiniteFactor
symmetricPowerLaw(double, double) - Static method in class jdistlib.DiscreteTailBounds: Power-law bound suitable for either outward tail around zero.
SYR - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SYR2 - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SYR2K - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SYRK - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
SYTRF - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation

T

T - Class in jdistlib
T(double) - Constructor for class jdistlib.T
t_test(double[], double[], double, boolean, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Two sample t-test
t_test(double[], double, TestKind) - Static method in class jdistlib.disttest.DistributionTest: One-sample t-test
t_test_paired(double[], double[], double, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Paired t-test
table(double[]) - Static method in class jdistlib.math.VectorMath
table(T[]) - Static method in class jdistlib.math.VectorMath
tabulate(int[], int) - Static method in class jdistlib.util.Utilities: Mimic the tabulate function in R
Tail - Enum Class in jdistlib.finance: Side of a scalar distribution used by tail and stress calculations.
tailEffectiveSampleSize() - Method in class jdistlib.inference.ParameterDiagnostics
tailProbability(double, Tail) - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
tan() - Method in class jdistlib.math.Complex
tanh() - Method in class jdistlib.math.Complex
tanh(int) - Method in class jdistlib.inference.autodiff.ReverseTape
TANH - Enum constant in enum class jdistlib.accelerator.UnaryOperation
TANH_SINH - Enum constant in enum class jdistlib.math.IntegrationOptions.Method: Double-exponential tanh-sinh quadrature for finite intervals.
tanhSinhMaxLevels(int) - Method in class jdistlib.math.IntegrationOptions.Builder
tanpi(double) - Static method in class jdistlib.math.MathFunctions
tape() - Method in class jdistlib.inference.autodiff.ReverseModeGradient
tape() - Method in class jdistlib.inference.autodiff.ReverseModeLogDensity
target() - Method in interface jdistlib.inference.SimulationBasedCalibration.Simulation
targetAcceptance() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
targetAcceptance() - Method in class jdistlib.inference.AdjustedMclmcTuningOptions
targetAcceptance() - Method in class jdistlib.inference.SamplingOptions
targetAcceptance(double) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
targetAcceptance(double) - Method in class jdistlib.inference.AdjustedMclmcTuningOptions.Builder
targetAcceptance(double) - Method in class jdistlib.inference.SamplingOptions.Builder
targetJumpAcceptance() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
targetJumpAcceptance() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
targetJumpAcceptance(double) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
targetJumpAcceptance(double) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
temperedLogDensity(double[]) - Method in interface jdistlib.inference.TemperedLogDensity
TemperedLogDensity - Interface in jdistlib.inference: Log density split into an untempered base (usually the prior) and likelihood.
terminalBuffer() - Method in class jdistlib.inference.WarmupSchedule.Resolved
terminalBuffer() - Method in class jdistlib.inference.WarmupSchedule
terminalDrawdown(GenericDistribution, int, int, long) - Static method in class jdistlib.finance.PathFunctionalDistributions
terminalPriceDistribution() - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
terminalProbability(double, Tail) - Method in class jdistlib.finance.OptionCurve
test(double) - Method in class jdistlib.disttest.online.LordPlusPlus
test(double) - Method in interface jdistlib.disttest.online.OnlineFdrController: Tests the next p-value and advances the controller exactly once.
test(double) - Method in class jdistlib.disttest.online.Saffron
TestKind - Enum Class in jdistlib.disttest
testRightCensored(double[], double, int, double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Tests a right-censored family, where every unrecorded p-value is known to be greater than censoringThreshold.
tetragamma(double) - Static method in class jdistlib.math.PolyGamma
tetragamma(double[]) - Static method in class jdistlib.math.PolyGamma
thinning() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
thinning() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
thinning() - Method in class jdistlib.inference.SamplingOptions
thinning() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
thinning(int) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
thinning(int) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
thinning(int) - Method in class jdistlib.inference.SamplingOptions.Builder
thinning(int) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
THOROUGH - Enum constant in enum class jdistlib.DiagnosticPreset
threshold(double[], double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Returns the largest observed raw p-value rejected at the requested level.
threshold(double[], double, MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Returns the raw rejection threshold for a declared total family size.
thresholdLog(double[], double, MultipleTesting.Method) - Static method in class jdistlib.disttest.MultipleTesting: Returns the largest rejected natural-log p-value, or NaN.
thresholdLog(double[], double, MultipleTesting.Method, int) - Static method in class jdistlib.disttest.MultipleTesting: Returns the log rejection threshold for a declared total family size.
thresholds(double[], double[]) - Static method in class jdistlib.finance.ExtremeValueInference
times(Polynomial) - Method in class jdistlib.math.Polynomial: Multiply this polynomial with another polynomial and store the result into a new instance of QPolynomial
timesEquals(Polynomial) - Method in class jdistlib.math.Polynomial: Multiply this polynomial with another polynomial, in place
timesScalar(double) - Method in class jdistlib.math.Polynomial: Multiply this polynomial with a constant and store the result into a new instance of QPolynomial
timesScalarEquals(double) - Method in class jdistlib.math.Polynomial: Multiply this polynomial with a constant, in place
title() - Method in class jdistlib.inference.ChartSpec
tn - Variable in class jdistlib.HyperGeometric.RandomState
to() - Method in class jdistlib.inference.ModelGraph.Edge
to_double(int[]) - Static method in class jdistlib.util.Utilities: Converts the integer array e into a double array
to_double_array(Collection<Double>) - Static method in class jdistlib.util.Utilities
to_int_array(Collection<Integer>) - Static method in class jdistlib.util.Utilities
toArray() - Method in class jdistlib.inference.lang.TupleValue
toBuilder() - Method in class jdistlib.FunctionAnalysisOptions: Returns a builder initialized from these settings.
toBuilder() - Method in class jdistlib.inference.SamplingOptions: Starts a builder that preserves every option, including streaming callbacks.
toBuilder() - Method in class jdistlib.math.IntegrationOptions: Returns a builder initialized from this object.
toCsv() - Method in class jdistlib.inference.ChartSpec
toCsv(String[], ChainResult...) - Static method in class jdistlib.inference.ChainExport
toCsv(ChartSpec) - Static method in class jdistlib.inference.InferenceGraphExport
toDense() - Method in class jdistlib.matrix.CsrMatrix: Returns a row-major dense matrix.
toDot(ModelGraph) - Static method in class jdistlib.inference.ModelGraphExport
toImmutable() - Method in class jdistlib.math.IntegrationResult: Creates an immutable modern snapshot without retaining IntegrationResult.f.
toJson() - Method in class jdistlib.DiagnosticFinding: Returns this finding as an RFC 8259 JSON object.
toJson() - Method in class jdistlib.DistributionAnalysis: Returns a versioned RFC 8259 JSON diagnostic report.
toJson() - Method in class jdistlib.FunctionAnalysis: Returns a versioned RFC 8259 JSON diagnostic report.
toJson() - Method in class jdistlib.inference.ChartSpec
toJson() - Method in class jdistlib.inference.McmcDiagnosticReport
toJson() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
toJson() - Method in class jdistlib.math.ImmutableIntegrationResult: Returns an RFC 8259 JSON diagnostic record.
toJson() - Method in class jdistlib.math.IntegrationResult: Returns an RFC 8259 JSON diagnostic record.
toJson() - Method in class jdistlib.math.IntegrationStabilityResult: Returns an RFC 8259 JSON diagnostic record.
toJson() - Method in class jdistlib.NumericalDistributionBuildResult: Returns the analysis and construction outcome as versioned JSON.
toJson(double) - Method in class jdistlib.inference.SparseSubsetSummary
toJson(String[], ChainResult...) - Static method in class jdistlib.inference.ChainExport
toJson(DiagnosticFinding) - Static method in class jdistlib.DiagnosticJson
toJson(DistributionAnalysis) - Static method in class jdistlib.DiagnosticJson
toJson(FunctionAnalysis) - Static method in class jdistlib.DiagnosticJson
toJson(ChartSpec) - Static method in class jdistlib.inference.InferenceGraphExport
toJson(McmcDiagnosticReport) - Static method in class jdistlib.inference.McmcJson
toJson(ModelGraph) - Static method in class jdistlib.inference.ModelGraphExport
toJson(ImmutableIntegrationResult) - Static method in class jdistlib.math.IntegrationJson
toJson(IntegrationResult) - Static method in class jdistlib.math.IntegrationJson
toJson(IntegrationStabilityResult) - Static method in class jdistlib.math.IntegrationJson
toJson(NumericalDistributionBuildResult) - Static method in class jdistlib.DiagnosticJson
tolerance - Variable in class jdistlib.inference.solver.AlgebraicSolver.Options
tolerance() - Method in class jdistlib.inference.PathfinderOptions
tolerance(double) - Method in class jdistlib.CdfTableOptions.Builder
tolerance(double) - Method in class jdistlib.inference.PathfinderOptions.Builder
toleranceFor(double) - Method in class jdistlib.MultivariateProbabilityOptions: Returns the convergence tolerance for a finite probability estimate.
tolerances(double, double) - Method in class jdistlib.math.IntegrationOptions.Builder
toModel() - Method in class jdistlib.inference.ReversibleJumpIterationStats
toSize() - Method in class jdistlib.inference.SparseSubsetIterationStats
toString() - Method in class jdistlib.DiagnosticFinding
toString() - Method in class jdistlib.inference.GradientCheckResult
toString() - Method in class jdistlib.inference.lang.ScriptDiagnostic
toString() - Method in class jdistlib.inference.lang.TupleValue
toString() - Method in class jdistlib.math.Complex
toString() - Method in class jdistlib.math.opt.OptimizationResult
toString() - Method in class jdistlib.math.Polynomial: Get a string representation of this polynomial with x as the variable name
toString() - Method in class jdistlib.math.spline.SmoothSplineResult: Debugging
toString() - Method in class jdistlib.matrix.CsrMatrix
toString(String) - Method in class jdistlib.math.Polynomial: Construct a string representation of this polynomial
toSvg(int, int) - Method in class jdistlib.inference.ChartSpec
toSvg(ChartSpec, int, int) - Static method in class jdistlib.inference.InferenceGraphExport
totalChains() - Method in class jdistlib.inference.SuperchainPlan
toTidyCsv(ReversibleJumpResult, ReversibleJumpTarget) - Static method in class jdistlib.inference.ReversibleJumpExport
trace(String, int, ChainResult...) - Static method in class jdistlib.inference.DiagnosticGraphs
trace(DifferentiableLogDensity, double[], int, int, double) - Static method in class jdistlib.inference.LbfgsOptimizer
transform(double[][], ToDoubleFunction<double[]>) - Static method in class jdistlib.inference.MonteCarloError
transform(GenericDistribution, UnivariateFunction, UnivariateFunction, UnivariateFunction, boolean, double, double) - Static method in class jdistlib.Distributions: Creates the distribution induced by a differentiable strictly monotone transformation of an existing distribution.
TransformDistribution - Interface in jdistlib.finance: Distribution exposing stable log characteristic and cumulant transforms.
TransformDomain - Class in jdistlib.finance: Open/closed interval on which a cumulant-generating function exists.
TransformDomain(double, boolean, double, boolean) - Constructor for class jdistlib.finance.TransformDomain
transitionCounts() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
TransitionKernel<S> - Interface in jdistlib.inference: Reusable one-step Markov kernel used by chains and meta-samplers.
TRANSPOSE - Enum constant in enum class jdistlib.accelerator.MatrixTranspose: Use the transpose of the stored matrix.
treeDepth() - Method in class jdistlib.inference.IterationStats
treeDepthSaturated() - Method in class jdistlib.inference.IterationStats
treeDepthSaturations() - Method in class jdistlib.inference.SamplerDiagnostics
Triangular - Class in jdistlib: Triangular distribution with minimum a, maximum b, and mode c.
Triangular(double, double, double) - Constructor for class jdistlib.Triangular
TRIANGULAR - Enum constant in enum class jdistlib.math.density.Kernel
trigamma(double) - Static method in class jdistlib.math.PolyGamma
trigamma(double[]) - Static method in class jdistlib.math.PolyGamma
trimean(double[]) - Static method in class jdistlib.math.VectorMath: Trimean (Q1 + 2Q2 + Q3) / 4
trimmed_mean(double[], double, double) - Static method in class jdistlib.math.VectorMath: Trimmed mean of values.
TRSM - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
TRSV - Enum constant in enum class jdistlib.accelerator.LinearAlgebraOperation
TRUE - Enum constant in enum class jdistlib.util.Bool3
trueParameters() - Method in interface jdistlib.inference.SimulationBasedCalibration.Simulation
trunc(double) - Static method in class jdistlib.math.MathFunctions
truncate(GenericDistribution, double, double) - Static method in class jdistlib.Distributions
TruncatedContinuousDistribution - Class in jdistlib: Continuous distribution conditioned to lie in a nonempty interval.
TruncatedContinuousDistribution(GenericDistribution, double, double) - Constructor for class jdistlib.TruncatedContinuousDistribution
Tukey - Class in jdistlib: Computes the probability and quantile that the maximum of rr studentized ranges, each based on cc means and with df degrees of freedom for the standard error, is less than q.
Tukey(double, double, double) - Constructor for class jdistlib.Tukey
TukeyLambda - Class in jdistlib: Tukey lambda distribution defined by its symmetric quantile function.
TukeyLambda(double) - Constructor for class jdistlib.TukeyLambda
tuneAndSample(LogDensity, double[], SamplingOptions, AdjustedMclmcTuningOptions, RandomEngine) - Static method in class jdistlib.inference.AdjustedMclmcTuner
TupleValue - Class in jdistlib.inference.lang: Immutable heterogeneous tuple for Java data adapters and external functions.
TupleValue(Object...) - Constructor for class jdistlib.inference.lang.TupleValue
Tweedie - Class in jdistlib: Translated from Tweedie package version 2.2.1, dated 2014-06-06, by Roby Joehanes
Tweedie(double, double, double) - Constructor for class jdistlib.Tweedie
TWO_SIDED - Enum constant in enum class jdistlib.disttest.TestKind
twoSided(UnivariateFunction, long, DiscreteTailBound, DiscreteTailBound, CertifiedDiscreteOptions) - Static method in class jdistlib.CertifiedInfiniteDiscreteDistribution: Constructs two-sided integer support around a finite center.
type() - Method in class jdistlib.inference.ChartSpec
type() - Method in class jdistlib.inference.MetricConfiguration

U

UCV - Static variable in class jdistlib.math.density.Bandwidth
unary(UnaryOperation, double[]) - Method in interface jdistlib.accelerator.ComputeBackend
unary(UnaryOperation, double[]) - Method in class jdistlib.accelerator.CpuComputeBackend
UnaryOperation - Enum Class in jdistlib.accelerator: Portable element-wise operations supported by accelerator backends.
unconstrain(double[], int, double[], int) - Method in interface jdistlib.inference.ParameterConstraint: Maps constrained values back to unconstrained coordinates.
unconstrain(Map<String, double[]>) - Method in class jdistlib.inference.BayesianModel: Converts a complete map of named constrained parameter values to sampler space.
unconstrained() - Method in class jdistlib.inference.DivergenceLocation
unconstrainedDimension() - Method in interface jdistlib.inference.ParameterConstraint
unconstrainedDimension() - Method in class jdistlib.inference.ParameterSpec
unconstrainedOffset() - Method in class jdistlib.inference.ParameterSpec
ungrouped(String...) - Static method in class jdistlib.inference.ObservationMetadata
Uniform - Class in jdistlib
Uniform(double, double) - Constructor for class jdistlib.Uniform
UniformRejectionEnvelope - Class in jdistlib: A uniform proposal for a finite interval with a certified density bound.
UniformRejectionEnvelope(double, double, double) - Constructor for class jdistlib.UniformRejectionEnvelope
UniformSparseCandidateProposal - Class in jdistlib.inference: Uniform proposal over currently inactive sparse candidates.
UniformSparseCandidateProposal() - Constructor for class jdistlib.inference.UniformSparseCandidateProposal
unique(double[]) - Static method in class jdistlib.util.Utilities
unique(S[]) - Static method in class jdistlib.util.Utilities
unit() - Static method in class jdistlib.inference.MetricConfiguration
UNIT - Enum constant in enum class jdistlib.accelerator.MatrixDiagonal
UNIT - Enum constant in enum class jdistlib.inference.MetricConfiguration.Type
unitVector(int) - Static method in class jdistlib.inference.Constraints: Stan-compatible unit-vector normalization transform.
UnivariateFunction - Interface in jdistlib.math: Abstraction of a function with one parameter
UNKNOWN - Enum constant in enum class jdistlib.math.IntegrationStatus
unreliableObservations() - Method in class jdistlib.inference.PsisLoo.Result
update(double[], double, LogDensity, MixedStateSpace, RandomEngine) - Method in class jdistlib.inference.ContinuousBlockMetropolisKernel
update(double[], double, LogDensity, MixedStateSpace, RandomEngine) - Method in class jdistlib.inference.DiscreteMetropolisKernel
update(double[], double, LogDensity, MixedStateSpace, RandomEngine) - Method in class jdistlib.inference.FiniteDiscreteGibbsKernel
update(double[], double, LogDensity, MixedStateSpace, RandomEngine) - Method in interface jdistlib.inference.HybridKernel
update(double[], LogDensity, RandomEngine) - Method in class jdistlib.inference.AdaptiveRejectionGibbsKernel
update(double[], LogDensity, RandomEngine) - Method in interface jdistlib.inference.GibbsKernel
update(double[], LogDensity, RandomEngine) - Method in class jdistlib.inference.MetropolisBlockKernel
update(int, int, boolean, IterationStats) - Method in interface jdistlib.inference.ProgressListener
update(int, int, boolean, IterationStats) - Method in class jdistlib.inference.WarmupTrace
update(int, int, boolean, ReversibleJumpIterationStats) - Method in interface jdistlib.inference.ReversibleJumpProgressListener
update(int, int, long, boolean, SparseSubsetIterationStats) - Method in interface jdistlib.inference.SparseSubsetProgressListener
update(ReversibleJumpState, double, ReversibleJumpTarget, RandomEngine, boolean) - Method in class jdistlib.inference.AdaptiveRjRandomWalkKernel
update(ReversibleJumpState, double, ReversibleJumpTarget, RandomEngine, boolean) - Method in class jdistlib.inference.FixedDimensionSamplerRjKernel
update(ReversibleJumpState, double, ReversibleJumpTarget, RandomEngine, boolean) - Method in class jdistlib.inference.ModelSpecificRjKernel
update(ReversibleJumpState, double, ReversibleJumpTarget, RandomEngine, boolean) - Method in interface jdistlib.inference.ReversibleJumpWithinModelKernel
upper() - Method in class jdistlib.inference.CoordinateSupport
UPPER - Enum constant in enum class jdistlib.accelerator.MatrixTriangle
UPPER - Enum constant in enum class jdistlib.finance.Tail
upperBound - Variable in class jdistlib.math.opt.OptimizationConfig
upperBound(double, int) - Static method in class jdistlib.inference.Constraints
upperBound(int) - Method in interface jdistlib.finance.DistributionFit.ParametricFamily
upperBound(long, double) - Method in interface jdistlib.DiscreteTailBound
upperConcentration(Copula, double) - Static method in class jdistlib.finance.CopulaTailAnalysis
upperQuantile() - Method in class jdistlib.inference.ParameterDiagnostics
upperTailAsymptotic(double) - Method in class jdistlib.finance.StableDistribution: Leading right-tail probability for large positive distance from location.
upperTailDependence(Copula) - Static method in class jdistlib.finance.CopulaTailAnalysis
Utilities - Class in jdistlib.util: Utility functions to mimic R
Utilities() - Constructor for class jdistlib.util.Utilities
Utilities.RankTies - Enum Class in jdistlib.util
Utils - Class in jdistlib.disttest
Utils() - Constructor for class jdistlib.disttest.Utils

V

v() - Method in enum class jdistlib.util.Bool3
vabs(double[]) - Static method in class jdistlib.math.VectorMath
valid() - Method in class jdistlib.inference.ReversibleJumpProposal
valid(ReversibleJumpState, String, double, double, double) - Static method in class jdistlib.inference.ReversibleJumpProposal
validate(DimensionMatchingTransformation, ReversibleJumpState, double[], double) - Static method in class jdistlib.inference.DimensionMatchingValidator
validate(SparseSubsetState) - Method in class jdistlib.inference.SparseSubsetTarget
validateStanSyntax(String) - Static method in class jdistlib.inference.lang.ModelScript: Validates Stan-compatible source without binding data or constructing a model.
validateSyntax(String) - Static method in class jdistlib.inference.lang.ModelScript: Parses the source without requiring data values or constructing a model.
value - Variable in class jdistlib.CopulaMeasureResult
value - Variable in exception class jdistlib.exception.PrecisionException
value() - Method in class jdistlib.inference.ModelEvaluationCache
value(double) - Method in interface jdistlib.finance.AdvancedRiskMeasures.Distortion
value(double[]) - Method in interface jdistlib.finance.DistributionFit.LogPrior
value(int) - Method in class jdistlib.inference.autodiff.ReverseTape
value(String, int) - Method in class jdistlib.inference.ModelState
value(GenericDistribution) - Method in interface jdistlib.finance.DistributionFit.CalibrationLoss
valueAt(int, int) - Method in class jdistlib.inference.ChainResult: Returns one retained unconstrained value without copying the chain.
valueAt(int, int) - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
valueAtRisk(double, RiskConvention) - Method in class jdistlib.finance.OptionInference.PosteriorEnsemble
valueAtRisk(GenericDistribution, double, RiskConvention) - Static method in class jdistlib.finance.FinancialRisk: Loss VaR at confidence level; returns are converted to losses first.
valueAtRiskInto(GenericDistribution, double[], int, double[], int, int, RiskConvention) - Static method in class jdistlib.finance.FinancialRisk
valueOf(String) - Static method in enum class jdistlib.accelerator.Compute: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.ComputeApi: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.ExecutionKind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.LinearAlgebraOperation: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.MatrixDiagonal: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.MatrixSide: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.MatrixTranspose: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.MatrixTriangle: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.NumericPrecision: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.SparseOrdering: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.accelerator.UnaryOperation: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.Binomial.BinomialKind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.ConstructionPolicy: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaDiagnostics.Classification: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaFamily: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaFitOptions.Method: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaFitResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaLikelihoodDiagnostics.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaLogLikelihoodResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaMarginal.Kind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaMeasureResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.CopulaSelectionCriterion: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.DiagnosticFinding.Severity: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.DiagnosticPreset: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.disttest.MultipleTesting.Method: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.disttest.TestKind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.finance.DistributionFit.Observation.Kind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.finance.ImpliedVolatilityResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.finance.OptionInference.Measure: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.finance.RiskConvention: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.finance.Tail: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.AdaptiveStaticHmcOptions.Criterion: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.ChainResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.ChartSpec.Type: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.ComputeNuts: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.CoordinateSupport.Kind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.HealthSeverity: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.MetricConfiguration.Type: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.ModelGraph.NodeKind: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.ReversibleJumpResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.SparseSubsetResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.inference.WarmupSchedule.Phase: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.math.approx.ApproximationType: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.math.density.Kernel: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.math.IntegrationOptions.CallbackExecution: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.math.IntegrationOptions.Method: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.math.IntegrationStatus: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.math.spline.SmoothSplineCriterion: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.MultivariateProbabilityStatus: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.RotatedCopula.Rotation: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.SamplingStrategy: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.util.Bool3: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.util.Utilities.RankTies: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.VineFitResult.Status: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class jdistlib.VineStructure: Returns the enum constant of this class with the specified name.
valueOrThrow() - Method in class jdistlib.finance.NumericalEstimate: Returns the value only after enforcing the checked-result contract.
values() - Static method in enum class jdistlib.accelerator.Compute: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.ComputeApi: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.ExecutionKind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.LinearAlgebraOperation: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.MatrixDiagonal: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.MatrixSide: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.MatrixTranspose: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.MatrixTriangle: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.NumericPrecision: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.SparseOrdering: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.accelerator.UnaryOperation: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.Binomial.BinomialKind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.ConstructionPolicy: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaDiagnostics.Classification: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaFamily: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaFitOptions.Method: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaFitResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaLikelihoodDiagnostics.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaLogLikelihoodResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaMarginal.Kind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaMeasureResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.CopulaSelectionCriterion: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.DiagnosticFinding.Severity: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.DiagnosticPreset: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.disttest.MultipleTesting.Method: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.disttest.TestKind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.finance.DistributionFit.Observation.Kind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.finance.ImpliedVolatilityResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.finance.OptionInference.Measure: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.finance.RiskConvention: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.finance.Tail: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.AdaptiveStaticHmcOptions.Criterion: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.ChainResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.ChartSpec.Type: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Method in class jdistlib.inference.ColumnarDraws
values() - Static method in enum class jdistlib.inference.ComputeNuts: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.CoordinateSupport.Kind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.HealthSeverity: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Method in class jdistlib.inference.lang.ExternalFunctionResult
values() - Static method in enum class jdistlib.inference.MetricConfiguration.Type: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.ModelGraph.NodeKind: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Method in class jdistlib.inference.PointwiseLogLikelihoodDraws
values() - Static method in enum class jdistlib.inference.ReversibleJumpResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Method in class jdistlib.inference.solver.SensitivityResult: Output values indexed by output point then state component.
values() - Static method in enum class jdistlib.inference.SparseSubsetResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.inference.WarmupSchedule.Phase: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.math.approx.ApproximationType: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.math.density.Kernel: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.math.IntegrationOptions.CallbackExecution: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.math.IntegrationOptions.Method: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.math.IntegrationStatus: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.math.spline.SmoothSplineCriterion: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Method in class jdistlib.matrix.CsrMatrix
values() - Method in class jdistlib.matrix.FloatCsrMatrix
values() - Static method in enum class jdistlib.MultivariateProbabilityStatus: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.RotatedCopula.Rotation: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.SamplingStrategy: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.util.Bool3: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.util.Utilities.RankTies: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.VineFitResult.Status: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class jdistlib.VineStructure: Returns an array containing the constants of this enum class, in the order they are declared.
var(double[]) - Static method in class jdistlib.math.VectorMath
var_test(double[], double[], double, TestKind) - Static method in class jdistlib.disttest.DistributionTest: Performs an F test to compare the variances of two samples from normal populations.
var_test(double[], double[], TestKind) - Static method in class jdistlib.disttest.DistributionTest: Performs an F test to compare the variances of two samples from normal populations.
variable(double) - Method in class jdistlib.inference.autodiff.ReverseTape
variableIndices() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Step
variableNames() - Method in class jdistlib.inference.ProjectionPredictiveSelection.Step
varianceGamma(double, double[], double[], double[][]) - Static method in class jdistlib.finance.MultivariateFinancialDistribution: Multivariate VG with shared Gamma(shape,1) mixer.
VarianceGammaDistribution - Class in jdistlib.finance: Variance-gamma law X=mu+theta*G+sigma*sqrt(G)*Z, G~Gamma(shape,1).
VarianceGammaDistribution(double, double, double, double) - Constructor for class jdistlib.finance.VarianceGammaDistribution
vcomp(double[]) - Static method in class jdistlib.math.VectorMath
vdiv(double[], double) - Static method in class jdistlib.math.VectorMath
vdiv(double[], double[]) - Static method in class jdistlib.math.VectorMath
vdiv(double, double[]) - Static method in class jdistlib.math.VectorMath
vector(String) - Method in class jdistlib.inference.ModelData
vector(String) - Method in class jdistlib.inference.ModelState
vectorInto(String, double[]) - Method in class jdistlib.inference.ModelData: Copies a vector into caller-owned storage without creating a temporary array.
VectorMath - Class in jdistlib.math
VectorMath() - Constructor for class jdistlib.math.VectorMath
velocities() - Method in class jdistlib.inference.solver.HigherIndexDaeSolver.Result
vendor() - Method in class jdistlib.accelerator.ComputeDeviceInfo
version() - Method in class jdistlib.inference.SamplerCheckpoint
vexp(double[]) - Static method in class jdistlib.math.VectorMath
VineCopula - Interface in jdistlib: Common contract for pair-copula vine constructions.
VineFitResult - Class in jdistlib: Result of sequential pair-family selection for a simplified vine.
VineFitResult.Status - Enum Class in jdistlib
VineFitter - Class in jdistlib: Sequential simplified C-vine and D-vine fitting with pair-family selection.
VineProbabilityResult - Class in jdistlib: Monte Carlo lower-orthant probability returned by a vine copula.
VineStructure - Enum Class in jdistlib: Simplified regular-vine structures implemented by JDistlib.
vlog(double[]) - Static method in class jdistlib.math.VectorMath
vlog1pComps(double[]) - Static method in class jdistlib.math.VectorMath
vmin(double[]) - Static method in class jdistlib.math.VectorMath
vmin(double[], double) - Static method in class jdistlib.math.VectorMath
vmin(double[], double[]) - Static method in class jdistlib.math.VectorMath
vmin(double, double[]) - Static method in class jdistlib.math.VectorMath
vplus(double[], double) - Static method in class jdistlib.math.VectorMath
vplus(double[], double[]) - Static method in class jdistlib.math.VectorMath
vplus(double, double[]) - Static method in class jdistlib.math.VectorMath
vpow(double[], double) - Static method in class jdistlib.math.VectorMath
vpow(double[], double[]) - Static method in class jdistlib.math.VectorMath
vpow(double, double[]) - Static method in class jdistlib.math.VectorMath
vpow(double, int[]) - Static method in class jdistlib.math.VectorMath
vpow(int[], int[]) - Static method in class jdistlib.math.VectorMath
vsgn(double[]) - Static method in class jdistlib.math.VectorMath: Vector signum.
vsgn(int[]) - Static method in class jdistlib.math.VectorMath
vsignif(double[], int) - Static method in class jdistlib.math.VectorMath
vsq(double[]) - Static method in class jdistlib.math.VectorMath
vtimes(double[], double) - Static method in class jdistlib.math.VectorMath
vtimes(double[], double[]) - Static method in class jdistlib.math.VectorMath
vtimes(double, double[]) - Static method in class jdistlib.math.VectorMath
VULKAN - Enum constant in enum class jdistlib.accelerator.Compute: Require the optional Vulkan compute provider.
VULKAN - Enum constant in enum class jdistlib.accelerator.ComputeApi

W

w - Variable in class jdistlib.Ansari
w - Variable in class jdistlib.HyperGeometric.RandomState
w - Variable in class jdistlib.SignRank
w - Variable in class jdistlib.Wilcoxon
waic() - Method in class jdistlib.inference.Waic.Result
Waic - Class in jdistlib.inference: Widely applicable information criterion from pointwise log-likelihood draws.
Waic.Result - Class in jdistlib.inference
WALKER_ALIAS - Enum constant in enum class jdistlib.SamplingStrategy
wang(double) - Static method in class jdistlib.finance.AdvancedRiskMeasures: Exponential Wang distortion g(p)=Phi(Phi^-1(p)+shift).
warmup() - Method in class jdistlib.inference.ChainResult
warmupAcceptanceSum() - Method in class jdistlib.inference.SamplerCheckpoint
WarmupBundle - Class in jdistlib.inference: Fingerprinted metric/step-size warmup reuse, treated as an initial guess by default.
warmupComplete() - Method in class jdistlib.inference.ReversibleJumpCheckpoint
warmupComplete() - Method in class jdistlib.inference.SparseSubsetCheckpoint
warmupIteration() - Method in class jdistlib.inference.SamplerCheckpoint
warmupIterations() - Method in class jdistlib.inference.AdaptiveStaticHmcOptions
warmupIterations() - Method in class jdistlib.inference.ReversibleJumpSamplingOptions
warmupIterations() - Method in class jdistlib.inference.SamplingOptions
warmupIterations() - Method in class jdistlib.inference.SparseSubsetCheckpoint
warmupIterations() - Method in class jdistlib.inference.SparseSubsetSamplingOptions
warmupIterations(int) - Method in class jdistlib.inference.AdaptiveStaticHmcOptions.Builder
warmupIterations(int) - Method in class jdistlib.inference.ReversibleJumpSamplingOptions.Builder
warmupIterations(int) - Method in class jdistlib.inference.SamplingOptions.Builder
warmupIterations(long) - Method in class jdistlib.inference.SparseSubsetSamplingOptions.Builder
WarmupResult - Class in jdistlib.inference: Immutable summary of MCMC adaptation.
WarmupResult(int, double, double, double[], double) - Constructor for class jdistlib.inference.WarmupResult
warmupSchedule() - Method in class jdistlib.inference.SamplingOptions
warmupSchedule(WarmupSchedule) - Method in class jdistlib.inference.SamplingOptions.Builder
WarmupSchedule - Class in jdistlib.inference: Stan-style fast/slow/final warmup schedule with expanding metric windows.
WarmupSchedule(int, int, int) - Constructor for class jdistlib.inference.WarmupSchedule
WarmupSchedule.Phase - Enum Class in jdistlib.inference
WarmupSchedule.Resolved - Class in jdistlib.inference
WarmupTrace - Class in jdistlib.inference: Progress listener retaining lightweight step-size and schedule traces.
WarmupTrace(int, WarmupSchedule) - Constructor for class jdistlib.inference.WarmupTrace
WarmupTrace.Entry - Class in jdistlib.inference
warmupUpdate(int, double, ReversibleJumpState, boolean) - Method in class jdistlib.inference.AdaptiveGaussianRjBirthProposal
warmupUpdate(int, double, ReversibleJumpState, boolean) - Method in interface jdistlib.inference.RjBirthProposal
warmupUpdate(ReversibleJumpState, ReversibleJumpProposal, ReversibleJumpTarget, boolean) - Method in interface jdistlib.inference.ReversibleJumpMove
warmupUpdate(ReversibleJumpState, ReversibleJumpProposal, ReversibleJumpTarget, boolean) - Method in class jdistlib.inference.SubsetBirthMove
warmupUpdate(ReversibleJumpState, ReversibleJumpProposal, ReversibleJumpTarget, boolean) - Method in class jdistlib.inference.SubsetDeathMove
warmupUpdate(ReversibleJumpState, ReversibleJumpProposal, ReversibleJumpTarget, boolean) - Method in class jdistlib.inference.SubsetSwapMove
WARNING - Enum constant in enum class jdistlib.ConstructionPolicy: Errors prevent construction; warnings are retained in the report.
WARNING - Enum constant in enum class jdistlib.DiagnosticFinding.Severity
WARNING - Enum constant in enum class jdistlib.inference.HealthSeverity
warningAsError - Static variable in class jdistlib.util.Debug: Set to true if JDistlib should throw an exception if there is convergence / precision problem.
warnings() - Method in class jdistlib.inference.ChainResult
warnings() - Method in class jdistlib.inference.McmcDiagnosticReport
warnings() - Method in class jdistlib.inference.ReversibleJumpDiagnosticReport
warnings() - Method in class jdistlib.inference.ReversibleJumpResult
warnings() - Method in class jdistlib.inference.SparseSubsetResult
Weibull - Class in jdistlib
Weibull(double, double) - Constructor for class jdistlib.Weibull
weight(double) - Method in interface jdistlib.finance.AdvancedRiskMeasures.SpectralWeight
weightedCandidates() - Method in class jdistlib.inference.PathfinderFit
weightedLogLikelihood(Copula, double[][], double) - Static method in class jdistlib.finance.CopulaTailAnalysis: Tail-weighted pseudo log likelihood for comparison/fitting objectives.
weightedSum(GenericDistribution[], double[], int, long) - Static method in class jdistlib.finance.DistributionAggregation
weights() - Method in class jdistlib.inference.PredictiveStacking.Result
weights(UnivariateFunction) - Method in class jdistlib.NumericalDiscreteDistribution.Builder
which(boolean[]) - Static method in class jdistlib.util.Utilities
which_max(double[]) - Static method in class jdistlib.math.VectorMath
which_max(int[]) - Static method in class jdistlib.math.VectorMath
which_min(double[]) - Static method in class jdistlib.math.VectorMath
which_min(int[]) - Static method in class jdistlib.math.VectorMath
Wiener - Class in jdistlib: Four-parameter Wiener first-passage (drift-diffusion) density used by Stan.
Wilcoxon - Class in jdistlib: SYNOPSIS #include <Rmath.h> double dwilcox(double x, double m, double n, int give_log) double pwilcox(double x, double m, double n, int lower_tail, int log_p) double qwilcox(double x, double m, double n, int lower_tail, int log_p); double rwilcox(double m, double n) DESCRIPTION dwilcox The density of the Wilcoxon distribution.
Wilcoxon(int, int) - Constructor for class jdistlib.Wilcoxon
wilcoxon_test(double[], double, boolean, TestKind) - Static method in class jdistlib.disttest.DistributionTest: One-sample Wilcoxon test.
wilcoxon_test(double[], double, boolean, TestKind, double, double) - Static method in class jdistlib.disttest.DistributionTest: One-sample Wilcoxon signed-rank test with R-compatible preprocessing.
winsor_mean(double[], double, double) - Static method in class jdistlib.math.VectorMath: Winsorized mean of values.
Wishart - Class in jdistlib: Wishart distribution on symmetric positive-definite matrices.
withDegreesOfFreedomRange(double, double) - Method in class jdistlib.CopulaFitOptions
withDerivativeSteps(double, double) - Method in class jdistlib.CopulaMeasureOptions
withFrequencyRange(double, double) - Method in class jdistlib.finance.FourierInversionOptions
withinAccepted() - Method in class jdistlib.inference.SparseSubsetIterationStats
withinAccepts() - Method in class jdistlib.inference.ReversibleJumpIterationStats
withinAttempts() - Method in class jdistlib.inference.ReversibleJumpIterationStats
withInitialInverseMassMatrix(double[][]) - Method in class jdistlib.inference.MetricConfiguration
withInverseMassMatrix(int, double, double, double[][], double) - Static method in class jdistlib.inference.WarmupResult
withMaxCdfEvaluations(int) - Method in class jdistlib.CopulaMeasureOptions
withMaximumRefinements(int) - Method in class jdistlib.finance.FourierInversionOptions
withMember(int, Object) - Method in class jdistlib.inference.lang.TupleValue
withMethod(CopulaFitOptions.Method) - Method in class jdistlib.CopulaFitOptions
withNegativeTolerance(double) - Method in class jdistlib.CopulaMeasureOptions
withOptimizationIterations(int) - Method in class jdistlib.CopulaFitOptions
withoutAnalysis() - Method in class jdistlib.NumericalContinuousDistribution.Builder
withPanels(int) - Method in class jdistlib.finance.FourierInversionOptions
withPointwiseLikelihood(ObservationMetadata, PointwiseLogLikelihoodEvaluator) - Method in class jdistlib.inference.BayesianModel: Returns a copy of this model with an additional pointwise likelihood evaluator.
withTolerance(double) - Method in class jdistlib.finance.FourierInversionOptions
worstCoordinate() - Method in class jdistlib.inference.GradientCheckResult
write(Path, ChainCheckpoint, String, String) - Static method in class jdistlib.inference.CheckpointIO
write(Path, ReversibleJumpCheckpoint, String, String) - Static method in class jdistlib.inference.ReversibleJumpCheckpointIO
writeAtomic(Path, SparseSubsetCheckpoint, String, String) - Static method in class jdistlib.inference.SparseSubsetCheckpointIO
writeState(DataOutputStream) - Method in class jdistlib.rng.MersenneTwister: Writes the entire state of the MersenneTwister RNG to the stream
writeState(DataOutputStream) - Method in class jdistlib.rng.MersenneTwisterSafe: Writes the entire state of the MersenneTwister RNG to the stream
writeTidySegmentAtomic(Path, SparseSubsetResult, SparseSubsetTarget, long) - Static method in class jdistlib.inference.SparseSubsetExport

X

x - Variable in class jdistlib.math.density.Density
x() - Method in class jdistlib.inference.ChartSpec.Series
xAt(int) - Method in class jdistlib.inference.ChartSpec.Series: Returns one horizontal coordinate without copying the series.
xi - Variable in class jdistlib.Tweedie
xl - Variable in class jdistlib.Binomial.RandomState
xl - Variable in class jdistlib.HyperGeometric.RandomState
xLabel() - Method in class jdistlib.inference.ChartSpec
xll - Variable in class jdistlib.Binomial.RandomState
xlr - Variable in class jdistlib.Binomial.RandomState
xm - Variable in class jdistlib.Binomial.RandomState
xr - Variable in class jdistlib.Binomial.RandomState
xr - Variable in class jdistlib.HyperGeometric.RandomState

Y

y - Variable in class jdistlib.math.density.Density
y() - Method in class jdistlib.inference.ChartSpec.Series
y(double, double) - Static method in class jdistlib.math.Bessel: This routine calculates Bessel functions Y_{alpha} (x) for non-negative argument X, and order alpha.
yAt(int) - Method in class jdistlib.inference.ChartSpec.Series: Returns one vertical coordinate without copying the series.
yLabel() - Method in class jdistlib.inference.ChartSpec

Z

ZERO - Static variable in class jdistlib.math.Complex
ZERO_LIKELIHOOD - Enum constant in enum class jdistlib.CopulaLogLikelihoodResult.Status
zeroin(UnivariateFunction, double, double, double, int) - Static method in class jdistlib.math.opt.Optimization: ************************************************************************ C math library function ZEROIN - obtain a function zero within the given range Output Zeroin returns an estimate for the root with accuracy 4*EPSILON*abs(x) + tol Algorithm G.Forsythe, M.Malcolm, C.Moler, Computer methods for mathematical computations.
ZeroInflatedNegativeBinomial - Class in jdistlib: Mean/size negative binomial with an additional structural-zero probability.
ZeroInflatedNegativeBinomial(double, double, double) - Constructor for class jdistlib.ZeroInflatedNegativeBinomial
ZeroInflatedPoisson - Class in jdistlib: Poisson distribution with an additional structural-zero probability.
ZeroInflatedPoisson(double, double) - Constructor for class jdistlib.ZeroInflatedPoisson
ZeroTruncatedNegativeBinomial - Class in jdistlib: Mean/size negative binomial conditional on a positive count.
ZeroTruncatedNegativeBinomial(double, double) - Constructor for class jdistlib.ZeroTruncatedNegativeBinomial
ZeroTruncatedPoisson - Class in jdistlib: Poisson distribution conditional on a positive count.
ZeroTruncatedPoisson(double) - Constructor for class jdistlib.ZeroTruncatedPoisson
Zipf - Class in jdistlib: Zipf distribution Parts taken from VGAM
Zipf(int, double) - Constructor for class jdistlib.Zipf

_

_expm1(double) - Static method in class jdistlib.math.MathFunctions: Alternative expm1 -- no difference from Java's
_log1p(double) - Static method in class jdistlib.math.MathFunctions: Alternative log1p.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form