npstat::LOrPECopulaSmoother< MaxLOrPEDeg > Class Template Reference

#include <LOrPECopulaSmoother.hh>

Inheritance diagram for npstat::LOrPECopulaSmoother< MaxLOrPEDeg >:

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

Public Member Functions
	LOrPECopulaSmoother (const unsigned *nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, const AbsDistributionND &kernel, const double *taper, unsigned maxDegree, double initialBw, const typename Base::CVCalc *cvCalc, bool becomeCvCalcOwner, double cvRange, unsigned nCV, bool useConvolve)
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< LocalPolyFilterND< MaxLOrPEDeg > >
	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

template<unsigned MaxLOrPEDeg>
class npstat::LOrPECopulaSmoother< MaxLOrPEDeg >

This class builds multivariate filters for copula smoothing which utilize systems of discrete orthogonal multivariate polynomials

Constructor & Destructor Documentation

LOrPECopulaSmoother()

template<unsigned MaxLOrPEDeg>

npstat::LOrPECopulaSmoother< MaxLOrPEDeg >::LOrPECopulaSmoother	(	const unsigned *	nBinsInEachDim,
		unsigned	dim,
		double	marginTolerance,
		unsigned	maxNormCycles,
		const AbsDistributionND &	kernel,
		const double *	taper,
		unsigned	maxDegree,
		double	initialBw,
		const typename Base::CVCalc *	cvCalc,
		bool	becomeCvCalcOwner,
		double	cvRange,
		unsigned	nCV,
		bool	useConvolve
	)

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

kernel – kernel to use for generating the filters. This should be a standard kernel, with location of 0 in each dimension. The scales should normally be set to 1 (unless you want different scale factors for different dimensions).

taper, maxDegree – LocalPolyFilterND parameters

initialBw – "central" bandwidth for cross validation calculations (or the actual bandwidth used in case cross validation is not performed). Set this parameter to 0.0 in order to disable filtering altogether.

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 the destructor of the base class.

cvRange – we will scan bandwidth values between initialBw/cvRange and initialBw*cvRange uniformly in the log space.

nCV – number of bandwidth values to try in the bandwidth scan. If this number is even, it will be increased by 1 internally so that the "central" bandwidth is included in the scan. If this parameter is 0 or 1, the value given by "initialBw" will be used.

useConvolve – if "true", use "convolve" method of the filter rather than "filter" method.

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

• stat/LOrPECopulaSmoother.hh