#include <SequentialCopulaSmoother.hh>

Inheritance diagram for npstat::SequentialCopulaSmoother:

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
	SequentialCopulaSmoother (const unsigned nBinsInEachDim, unsigned dim, double marginTolerance, unsigned maxNormCycles, int symbetaPower, double maxFilterDegree, const BoundaryHandling &boundaryMethod, double initialBw, const double bwCoeffs, const CVCalc *cvCalc, bool becomeCvCalcOwner, double cvRange, unsigned nCV, bool useConvolve, bool doublyStochastic=true)

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

◆ SequentialCopulaSmoother()

npstat::SequentialCopulaSmoother::SequentialCopulaSmoother	(	const unsigned *	nBinsInEachDim,
		unsigned	dim,
		double	marginTolerance,
		unsigned	maxNormCycles,
		int	symbetaPower,
		double	maxFilterDegree,
		const BoundaryHandling &	boundaryMethod,
		double	initialBw,
		const double *	bwCoeffs,
		const CVCalc *	cvCalc,
		bool	becomeCvCalcOwner,
		double	cvRange,
		unsigned	nCV,
		bool	useConvolve,
		bool	doublyStochastic = `true`
	)

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

symbetaPower – these parameters will be passed to the maxFilterDegree "symbetaLOrPEFilter1D" function when the boundaryMethod filters will be constructed

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.

bwCoeffs – bandwidth factors for each dimension. This array must have "dim" positive numbers. The argument can also be NULL in which case it is assumed that all factors are 1.0.

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

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.

doublyStochastic – if "true", a doubly stochastic approximation will be derived for every original filter

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

stat/SequentialCopulaSmoother.hh

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ SequentialCopulaSmoother()