Package org.drip.sequence.custom

Class KernelDensityEstimationL1

java.lang.Object

org.drip.function.definition.RdToR1

org.drip.sequence.functional.MultivariateRandom

org.drip.sequence.functional.BoundedMultivariateRandom

org.drip.sequence.custom.KernelDensityEstimationL1

public class KernelDensityEstimationL1
extends BoundedMultivariateRandom

KernelDensityEstimationL1 implements the L1 Error Scheme Estimation for a Multivariate Kernel Density Estimator with Focus on establishing targeted Variate-Specific and Agnostic Bounds.

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

Author:

Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor	Description
KernelDensityEstimationL1(R1ToR1 auKernel, double dblSmoothingParameter, int iSampleSize, R1ToR1 auResponse)	KernelDensityEstimationL1 Constructor

Method Summary

Modifier and Type	Method	Description
int	dimension()	Retrieve the Dimension of the Input Variate
double	evaluate(double[] adblVariate)	Evaluate for the given Input Variates
R1ToR1	kernelFunction()	Retrieve the Kernel Function
R1ToR1	responseFunction()	Retrieve the Response Function
int	sampleSize()	Retrieve the Sample Size
double	smoothingParameter()	Retrieve the Smoothing Parameter
double	targetVariateVarianceBound(int iTargetVariateIndex)	Retrieve the Maximal Agnostic Variance Bound over the Non-target Variate Space for the Target Variate

Methods inherited from class org.drip.sequence.functional.MultivariateRandom

conditionalTargetVariateMetrics, conditionalTargetVariateMetrics, ghostTargetVariateMetrics, ghostTargetVariateMetrics, ghostTargetVariateMetrics, unconditionalTargetVariateMetrics

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

conditionNumber, conditionNumberL2, conditionNumberLInfinity, conditionNumberLp, derivative, differential, 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

Constructor Details

KernelDensityEstimationL1

public KernelDensityEstimationL1(R1ToR1 auKernel,
double dblSmoothingParameter,
int iSampleSize,
R1ToR1 auResponse)
                          throws java.lang.Exception

KernelDensityEstimationL1 Constructor

Parameters:

auKernel - The Kernel Function

dblSmoothingParameter - The Smoothing Parameter

iSampleSize - The Sample Size

auResponse - The Response Function

Throws:

java.lang.Exception - Thrown if Inputs are Invalid

Method Details

kernelFunction

public R1ToR1 kernelFunction()

Retrieve the Kernel Function

Returns:

The Kernel Function

smoothingParameter

public double smoothingParameter()

Retrieve the Smoothing Parameter

Returns:

The Smoothing Parameter

sampleSize

public int sampleSize()

Retrieve the Sample Size

Returns:

The Sample Size

responseFunction

public R1ToR1 responseFunction()

Retrieve the Response Function

Returns:

The Response Function

dimension

public int dimension()

Description copied from class: RdToR1

Retrieve the Dimension of the Input Variate

Specified by:

dimension in class RdToR1

Returns:

The Dimension of the Input Variate

evaluate

public double evaluate(double[] adblVariate)
                throws java.lang.Exception

Description copied from class: RdToR1

Evaluate for the given Input Variates

Specified by:

evaluate in class RdToR1

Parameters:

adblVariate - Array of Input Variates

Returns:

The Calculated Value

Throws:

java.lang.Exception - Thrown if the Evaluation cannot be done

targetVariateVarianceBound

public double targetVariateVarianceBound(int iTargetVariateIndex)
                                  throws java.lang.Exception

Description copied from class: BoundedMultivariateRandom

Retrieve the Maximal Agnostic Variance Bound over the Non-target Variate Space for the Target Variate

Specified by:

targetVariateVarianceBound in class BoundedMultivariateRandom

Parameters:

iTargetVariateIndex - The Index corresponding to the Variate on which the Bound is sought

Returns:

The Maximal Agnostic Bound over the Non-target Variate Space for the Target Variate

Throws:

java.lang.Exception - Thrown if the Inputs are invalid