Package jdistlib.inference

Class MonteCarloError

java.lang.Object

jdistlib.inference.MonteCarloError

public final class MonteCarloError
extends Object

MCSE and efficiency helpers for one stationary retained sequence.

Method Summary

Modifier and Type	Method	Description
static double	effectiveSampleSize(double[] values)
static double	essPerEvaluation(double ess, long evaluations)
static double	essPerSecond(double ess, long elapsedNanoseconds)
static double	functionEss(double[][] samples, ToDoubleFunction<double[]> function)
static double	functionMcse(double[][] samples, ToDoubleFunction<double[]> function)
static double	indicatorEss(double[][] samples, Predicate<double[]> predicate)
static double	meanMcse(double[] values)
static double	quantileMcse(double[] values, double probability)
static double	standardDeviationMcse(double[] values)
static double[]	transform(double[][] samples, ToDoubleFunction<double[]> function)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

effectiveSampleSize

public static double effectiveSampleSize(double[] values)

standardDeviationMcse

public static double standardDeviationMcse(double[] values)

meanMcse

public static double meanMcse(double[] values)

functionEss

public static double functionEss(double[][] samples,
 ToDoubleFunction<double[]> function)

functionMcse

public static double functionMcse(double[][] samples,
 ToDoubleFunction<double[]> function)

indicatorEss

public static double indicatorEss(double[][] samples,
 Predicate<double[]> predicate)

transform

public static double[] transform(double[][] samples,
 ToDoubleFunction<double[]> function)

quantileMcse

public static double quantileMcse(double[] values,
 double probability)

essPerEvaluation

public static double essPerEvaluation(double ess,
 long evaluations)

essPerSecond

public static double essPerSecond(double ess,
 long elapsedNanoseconds)