Package org.drip.sequence.functional

Class MultivariateRandom

java.lang.Object

org.drip.function.definition.RdToR1

org.drip.sequence.functional.MultivariateRandom

Direct Known Subclasses:

BoundedMultivariateRandom, FlatMultivariateRandom, GlivenkoCantelliFunctionSupremum

public abstract class MultivariateRandom
extends RdToR1

MultivariateRandom contains the implementation of the objective Function dependent on Multivariate Random Variables.

• Module = Numerical Core Module
• Library = Statistical Learning Library
• Project = Sequence
• Package = Functional

Author:

Lakshmi Krishnamurthy

Method Summary

Modifier and Type	Method	Description
SingleSequenceAgnosticMetrics	conditionalTargetVariateMetrics(double[] adblNonTargetVariate, int iTargetVariateIndex, SingleSequenceAgnosticMetrics ssamTarget)	Compute the Target Variate Function Metrics Conditional on the specified Input Non-Target Variate Parameter Sequence
SingleSequenceAgnosticMetrics	conditionalTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM, int[] aiNonTargetVariateSequenceIndex, int iTargetVariateIndex)	Compute the Target Variate Function Metrics Conditional on the specified Input Non-target Variate Parameter Sequence
SingleSequenceAgnosticMetrics	ghostTargetVariateMetrics(double[] adblNonTargetVariate, int iTargetVariateIndex, double[] adblTargetVariateGhostSample)	Compute the Target Variate Function Metrics conditional on the specified Input Non-Target Variate Parameter Sequence Off of the Target Variate Ghost Sample Sequence
SingleSequenceAgnosticMetrics	ghostTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM, int[] aiNonTargetVariateSequenceIndex, int iTargetVariateIndex, double[] adblTargetVariateGhostSample)	Compute the Target Variate Function Metrics conditional on the specified Input Non-Target Variate Parameter Sequence Off of the Target Variate Ghost Sample Sequence
SingleSequenceAgnosticMetrics	ghostTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM, int iTargetVariateIndex, double[] adblTargetVariateGhostSample)	Compute the Target Variate Function Metrics over the full Non-target Variate Empirical Distribution Off of the Target Variate Ghost Sample Sequence
SingleSequenceAgnosticMetrics	unconditionalTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM, int iTargetVariateIndex)	Compute the Target Variate Function Metrics over the full Non-target Variate Empirical Distribution

Methods inherited from class org.drip.function.definition.RdToR1

derivative, differential, dimension, evaluate, gradient, gradientModulus, gradientModulusFunction, hessian, integrate, jacobian, maxima, minima, ValidateInput

Methods inherited from class java.lang.Object

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

Method Details

ghostTargetVariateMetrics

public SingleSequenceAgnosticMetrics ghostTargetVariateMetrics(double[] adblNonTargetVariate,
int iTargetVariateIndex,
double[] adblTargetVariateGhostSample)

Compute the Target Variate Function Metrics conditional on the specified Input Non-Target Variate Parameter Sequence Off of the Target Variate Ghost Sample Sequence

Parameters:

adblNonTargetVariate - The Non-Target Variate Parameters

iTargetVariateIndex - Target Variate Index

adblTargetVariateGhostSample - Target Variate Ghost Sample

Returns:

The Variate-specific Function Metrics

ghostTargetVariateMetrics

public SingleSequenceAgnosticMetrics ghostTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM,
int[] aiNonTargetVariateSequenceIndex,
int iTargetVariateIndex,
double[] adblTargetVariateGhostSample)

Compute the Target Variate Function Metrics conditional on the specified Input Non-Target Variate Parameter Sequence Off of the Target Variate Ghost Sample Sequence

Parameters:

aSSAM - Array of Variate Sequence Metrics

aiNonTargetVariateSequenceIndex - Array of Non-Target Variate Sequence Indexes

iTargetVariateIndex - Target Variate Index

adblTargetVariateGhostSample - Target Variate Ghost Sample

Returns:

The Variate-specific Function Metrics

ghostTargetVariateMetrics

public SingleSequenceAgnosticMetrics ghostTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM,
int iTargetVariateIndex,
double[] adblTargetVariateGhostSample)

Compute the Target Variate Function Metrics over the full Non-target Variate Empirical Distribution Off of the Target Variate Ghost Sample Sequence

Parameters:

aSSAM - Array of Variate Sequence Metrics

iTargetVariateIndex - Target Variate Index

adblTargetVariateGhostSample - Target Variate Ghost Sample

Returns:

The Variate-specific Function Metrics

conditionalTargetVariateMetrics

public SingleSequenceAgnosticMetrics conditionalTargetVariateMetrics(double[] adblNonTargetVariate,
int iTargetVariateIndex,
SingleSequenceAgnosticMetrics ssamTarget)

Compute the Target Variate Function Metrics Conditional on the specified Input Non-Target Variate Parameter Sequence

Parameters:

adblNonTargetVariate - The Non-Target Variate Parameters

iTargetVariateIndex - Target Variate Index

ssamTarget - Target Variate Metrics

Returns:

The Variate-specific Function Metrics

conditionalTargetVariateMetrics

public SingleSequenceAgnosticMetrics conditionalTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM,
int[] aiNonTargetVariateSequenceIndex,
int iTargetVariateIndex)

Compute the Target Variate Function Metrics Conditional on the specified Input Non-target Variate Parameter Sequence

Parameters:

aSSAM - Array of Variate Sequence Metrics

aiNonTargetVariateSequenceIndex - Array of Non-Target Variate Sequence Indexes

iTargetVariateIndex - Target Variate Index

Returns:

The Variate-specific Function Metrics

unconditionalTargetVariateMetrics

public SingleSequenceAgnosticMetrics unconditionalTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM,
int iTargetVariateIndex)

Compute the Target Variate Function Metrics over the full Non-target Variate Empirical Distribution

Parameters:

aSSAM - Array of Variate Sequence Metrics

iTargetVariateIndex - Target Variate Index

Returns:

The Variate-specific Function Metrics