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

#include <BandwidthCVLeastSquaresND.hh>

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

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

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

Detailed Description

template<typename Num, class Array>
struct npstat::BandwidthCVLeastSquaresND< 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::BandwidthCVLeastSquaresND< Num, Array >::operator() ( const HistoND< Num > &  histo, const Array &  densityEstimate, const AbsPolyFilterND &  filterUsed  ) const

virtual

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

"densityEstimate" is allowed to be an estimate without truncation (even if it includes negative values).

Implements npstat::AbsBandwidthCVND< Num, Array >.

operator()() [2/2]

template<typename Num , class Array >

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

virtual

Cross-validation for samples of multivariate weighted points

Implements npstat::AbsBandwidthCVND< Num, Array >.

---

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

• stat/BandwidthCVLeastSquaresND.hh