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
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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 SequenceSingleSequenceAgnosticMetrics
conditionalTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM, int[] aiNonTargetVariateSequenceIndex, int iTargetVariateIndex)
Compute the Target Variate Function Metrics Conditional on the specified Input Non-target Variate Parameter SequenceSingleSequenceAgnosticMetrics
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 SequenceSingleSequenceAgnosticMetrics
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 SequenceSingleSequenceAgnosticMetrics
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 SequenceSingleSequenceAgnosticMetrics
unconditionalTargetVariateMetrics(SingleSequenceAgnosticMetrics[] aSSAM, int iTargetVariateIndex)
Compute the Target Variate Function Metrics over the full Non-target Variate Empirical DistributionMethods inherited from class org.drip.function.definition.RdToR1
conditionNumber, conditionNumberL2, conditionNumberLInfinity, conditionNumberLp, 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
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Method Details
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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 ParametersiTargetVariateIndex
- Target Variate IndexadblTargetVariateGhostSample
- Target Variate Ghost Sample- Returns:
- The Variate-specific Function Metrics
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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 MetricsaiNonTargetVariateSequenceIndex
- Array of Non-Target Variate Sequence IndexesiTargetVariateIndex
- Target Variate IndexadblTargetVariateGhostSample
- Target Variate Ghost Sample- Returns:
- The Variate-specific Function Metrics
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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 MetricsiTargetVariateIndex
- Target Variate IndexadblTargetVariateGhostSample
- Target Variate Ghost Sample- Returns:
- The Variate-specific Function Metrics
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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 ParametersiTargetVariateIndex
- Target Variate IndexssamTarget
- Target Variate Metrics- Returns:
- The Variate-specific Function Metrics
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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 MetricsaiNonTargetVariateSequenceIndex
- Array of Non-Target Variate Sequence IndexesiTargetVariateIndex
- Target Variate Index- Returns:
- The Variate-specific Function Metrics
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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 MetricsiTargetVariateIndex
- Target Variate Index- Returns:
- The Variate-specific Function Metrics
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