This class is a variant of KernelDensityGen, but with a rescaling of the empirical distribution so that the variance of the density used to generate the random variates is equal to the empirical variance, as suggested by [207] . More...

Inheritance diagram for umontreal.ssj.randvar.KernelDensityVarCorrectGen:

Public Member Functions
	KernelDensityVarCorrectGen (RandomStream s, EmpiricalDist dist, RandomVariateGen kGen, double h, double sigmak2)
	Creates a new generator for a kernel density estimated from the observations given by the empirical distribution dist, using stream s to select the observations, generator kGen to generate the added noise from the kernel density, bandwidth h, and \(\sigma_k^2 =\) sigmak2 used for the variance correction.
	KernelDensityVarCorrectGen (RandomStream s, EmpiricalDist dist, NormalGen kGen)
	This constructor uses a gaussian kernel and the default bandwidth suggested in Table `kernels` for the gaussian distribution.
void	setBandwidth (double h)
	Sets the bandwidth to h.
double	nextDouble ()
	Generates a random number from the continuous distribution contained in this object.
Public Member Functions inherited from umontreal.ssj.randvar.KernelDensityGen
	KernelDensityGen (RandomStream s, EmpiricalDist dist, RandomVariateGen kGen, double h)
	Creates a new generator for a kernel density estimated from the observations given by the empirical distribution dist, using stream s to select the observations, generator kGen to generate the added noise from the kernel density, and bandwidth h.
	KernelDensityGen (RandomStream s, EmpiricalDist dist, NormalGen kGen)
	This constructor uses a gaussian kernel and the default bandwidth.
void	setPositiveReflection (boolean reflect)
	After this method is called with true, the generator will produce only positive values, by using the reflection method: replace all negative values by their absolute values.
Public Member Functions inherited from umontreal.ssj.randvar.RandomVariateGen
	RandomVariateGen (RandomStream s, Distribution dist)
	Creates a new random variate generator from the distribution dist, using stream s.
void	nextArrayOfDouble (double[] v, int start, int n)
	Generates n random numbers from the continuous distribution contained in this object.
double[]	nextArrayOfDouble (int n)
	Generates n random numbers from the continuous distribution contained in this object, and returns them in a new array of size n.
RandomStream	getStream ()
	Returns the umontreal.ssj.rng.RandomStream used by this generator.
void	setStream (RandomStream stream)
	Sets the umontreal.ssj.rng.RandomStream used by this generator to stream.
Distribution	getDistribution ()
	Returns the umontreal.ssj.probdist.Distribution used by this generator.
String	toString ()
	Returns a String containing information about the current generator.

Additional Inherited Members
static double	getBaseBandwidth (EmpiricalDist dist)
	Computes and returns the value of \(h_0\) in ( `bandwidth0` ).

Detailed Description

This class is a variant of KernelDensityGen, but with a rescaling of the empirical distribution so that the variance of the density used to generate the random variates is equal to the empirical variance, as suggested by [207] .

Let \(\bar{x}_n\) and \(s_n^2\) be the sample mean and sample variance of the observations. The distance between each generated random variate and the sample mean \(\bar{x}_n\) is multiplied by the correcting factor

\(1/\sigma_e\), where \(\sigma_e^2 = 1 + (h\sigma_k/s_n)^2\). The constant \(\sigma_k^2\) must be passed to the constructor. Its value can be found in Table kernels for some popular kernels.

Definition at line 51 of file KernelDensityVarCorrectGen.java.

Constructor & Destructor Documentation

◆ KernelDensityVarCorrectGen() [1/2]

umontreal.ssj.randvar.KernelDensityVarCorrectGen.KernelDensityVarCorrectGen	(	RandomStream	s,
		EmpiricalDist	dist,
		RandomVariateGen	kGen,
		double	h,
		double	sigmak2 )

Creates a new generator for a kernel density estimated from the observations given by the empirical distribution dist, using stream s to select the observations, generator kGen to generate the added noise from the kernel density, bandwidth h, and \(\sigma_k^2 =\) sigmak2 used for the variance correction.

Definition at line 64 of file KernelDensityVarCorrectGen.java.

◆ KernelDensityVarCorrectGen() [2/2]

umontreal.ssj.randvar.KernelDensityVarCorrectGen.KernelDensityVarCorrectGen	(	RandomStream	s,
		EmpiricalDist	dist,
		NormalGen	kGen )

This constructor uses a gaussian kernel and the default bandwidth suggested in Table kernels for the gaussian distribution.

Definition at line 78 of file KernelDensityVarCorrectGen.java.

Member Function Documentation

◆ nextDouble()

double umontreal.ssj.randvar.KernelDensityVarCorrectGen.nextDouble ( )

Generates a random number from the continuous distribution contained in this object.

By default, this method uses inversion by calling the umontreal.ssj.probdist.ContinuousDistribution.inverseF method of the distribution object. Alternative generating methods are provided in subclasses.