public class KernelDensityEstimationL1 extends BoundedMultivariateRandom
Constructor and Description |
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KernelDensityEstimationL1(R1ToR1 auKernel,
double dblSmoothingParameter,
int iSampleSize,
R1ToR1 auResponse)
KernelDensityEstimationL1 Constructor
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Modifier and Type | Method and Description |
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int |
dimension()
Retrieve the Dimension of the Input Variate
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double |
evaluate(double[] adblVariate)
Evaluate for the given Input Variates
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R1ToR1 |
kernelFunction()
Retrieve the Kernel Function
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R1ToR1 |
responseFunction()
Retrieve the Response Function
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int |
sampleSize()
Retrieve the Sample Size
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double |
smoothingParameter()
Retrieve the Smoothing Parameter
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double |
targetVariateVarianceBound(int iTargetVariateIndex)
Retrieve the Maximal Agnostic Variance Bound over the Non-target Variate Space for the Target Variate
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conditionalTargetVariateMetrics, conditionalTargetVariateMetrics, ghostTargetVariateMetrics, ghostTargetVariateMetrics, ghostTargetVariateMetrics, unconditionalTargetVariateMetrics
derivative, differential, gradient, gradientModulus, gradientModulusFunction, hessian, integrate, jacobian, maxima, minima, ValidateInput
public KernelDensityEstimationL1(R1ToR1 auKernel, double dblSmoothingParameter, int iSampleSize, R1ToR1 auResponse) throws java.lang.Exception
auKernel
- The Kernel FunctiondblSmoothingParameter
- The Smoothing ParameteriSampleSize
- The Sample SizeauResponse
- The Response Functionjava.lang.Exception
- Thrown if Inputs are Invalidpublic R1ToR1 kernelFunction()
public double smoothingParameter()
public int sampleSize()
public R1ToR1 responseFunction()
public int dimension()
RdToR1
public double evaluate(double[] adblVariate) throws java.lang.Exception
RdToR1
public double targetVariateVarianceBound(int iTargetVariateIndex) throws java.lang.Exception
BoundedMultivariateRandom
targetVariateVarianceBound
in class BoundedMultivariateRandom
iTargetVariateIndex
- The Index corresponding to the Variate on which the Bound is soughtjava.lang.Exception
- Thrown if the Inputs are invalid