npstat::BandwidthGCVLeastSquaresND< Num, Array > Struct Template Reference

#include <BandwidthGCVLeastSquaresND.hh>

Inheritance diagram for npstat::BandwidthGCVLeastSquaresND< Num, Array >:

Public Member Functions
virtual double	operator() (const HistoND< Num > &histo, const Array &densityEstimate, const Array &leaveOneOutEstimate, const AbsPolyFilterND &filterUsed) const
virtual double	operator() (const HistoND< Num > &histo, double effectiveSampleSize, const Array &densityEstimate, const Array &leaveOneOutEstimate, const AbsPolyFilterND &filterUsed) const

Additional Inherited Members
Public Types inherited from npstat::AbsBandwidthGCVND< Num, Array >
typedef Num	bin_type
typedef Array	density_type

Detailed Description

template<typename Num, class Array>
struct npstat::BandwidthGCVLeastSquaresND< Num, Array >

Class for calculating KDE or LOrPE cross-validation MISE approximations for multivariate density estimates. operator() returns -MISE estimate (a quantity to be maximized).

Member Function Documentation

operator()() [1/2]

template<typename Num , class Array >

virtual double npstat::BandwidthGCVLeastSquaresND< Num, Array >::operator() ( const HistoND< Num > &  histo, const Array &  densityEstimate, const Array &  leaveOneOutEstimate, const AbsPolyFilterND &  filterUsed  ) const

virtual

It should be assumed that the "nFillsInRange" method of the argument histogram returns the actual number of fills.

Implements npstat::AbsBandwidthGCVND< Num, Array >.

operator()() [2/2]

template<typename Num , class Array >

virtual double npstat::BandwidthGCVLeastSquaresND< Num, Array >::operator() ( const HistoND< Num > &  histo, double  effectiveSampleSize, const Array &  densityEstimate, const Array &  leaveOneOutEstimate, const AbsPolyFilterND &  filterUsed  ) const

virtual

Cross-validation for samples of multivariate weighted points

Implements npstat::AbsBandwidthGCVND< Num, Array >.

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

• stat/BandwidthGCVLeastSquaresND.hh