npstat::DiscreteGaussCopulaSmoother Class Reference

#include <DiscreteGaussCopulaSmoother.hh>

Inheritance diagram for npstat::DiscreteGaussCopulaSmoother:

Public Types
typedef CVCopulaSmoother< SequentialPolyFilterND >	Base
Public Types inherited from npstat::CVCopulaSmoother< SequentialPolyFilterND >
typedef AbsBandwidthCVND< double, ArrayND< double > >	CVCalc
typedef SequentialPolyFilterND	Filter

Public Member Functions
	DiscreteGaussCopulaSmoother (const unsigned *nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, const CVCalc *cvCalc, bool becomeCvCalcOwner, const Matrix< double > &bandwidthsToUse)
Public Member Functions inherited from npstat::AbsCVCopulaSmoother
bool	isConvolving () const
void	setConvolving (const bool b)
const std::vector< double > &	bandwidthValues () const
const std::vector< double > &	lastCVValues () const
const std::vector< double > &	lastRegularizedFractions () const
unsigned	getNFilters () const
unsigned	lastFilterChosen () const
Public Member Functions inherited from npstat::AbsCopulaSmootherBase
	AbsCopulaSmootherBase (const unsigned *nBinsInEachDim, unsigned dim, double tolerance, unsigned maxNormCycles)
unsigned	dim () const
ArrayShape	copulaShape () const
void	setArchive (gs::AbsArchive *ar, const char *category=0)
template<class Point >
const HistoND< double > &	smooth (unsigned long uniqueId, std::vector< OrderedPointND< Point > > &in, double *bandwidthUsed=0)
template<class Point >
const HistoND< double > &	weightedSmooth (unsigned long uniqueId, const std::vector< std::pair< const Point *, double > > &in, const unsigned *dimsToUse, unsigned nDimsToUse, double *bandwidthUsed=0)

Additional Inherited Members
Protected Member Functions inherited from npstat::CVCopulaSmoother< SequentialPolyFilterND >
	CVCopulaSmoother (const unsigned *nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, double initialBw, const CVCalc *cvCalc, bool becomeCvCalcOwner, double cvRange, unsigned nCV, bool useConvolve)
	CVCopulaSmoother (const unsigned *nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, const std::vector< double > &bandwidthValues, const CVCalc *cvCalc, bool becomeCvCalcOwner, bool useConvolve)
void	setFilter (unsigned i, Filter *filter)
Protected Member Functions inherited from npstat::AbsCVCopulaSmoother
	AbsCVCopulaSmoother (const unsigned *nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, double initialBw, double cvRange, unsigned nCV, bool useConvolve)
	AbsCVCopulaSmoother (const unsigned *nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, const std::vector< double > &bandwidthValues, bool useConvolve)

Detailed Description

This class builds multivariate copula filters which are tensor products of univariate filters

Constructor & Destructor Documentation

DiscreteGaussCopulaSmoother()

npstat::DiscreteGaussCopulaSmoother::DiscreteGaussCopulaSmoother	(	const unsigned *	nBinsInEachDim,
		unsigned	dim,
		double	marginTolerance,
		unsigned	maxNormCycles,
		const CVCalc *	cvCalc,
		bool	becomeCvCalcOwner,
		const Matrix< double > &	bandwidthsToUse
	)

Constructor arguments are as follows:

nBinsInEachDim – number of copula bins in each dimension

dim – copula dimensionality

marginTolerance – tolerance for the margin to be uniform

maxNormCycles – max number of copula normalization cycles

cvCalc – calculator for the quantity being optimized in the cross validation process. May be NULL in which case cross validation will not be used.

becomeCvCalcOwner – tells us whether we should destroy cvCalc in our own destructor

bandwidthsToUse – Bandwidth values to use. The row number of the matrix corresponds to the "trial" number and the column number gives the bandwidth for the corresponding dimension. All bandwidth values must be non-negative.

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The documentation for this class was generated from the following file:

• stat/DiscreteGaussCopulaSmoother.hh