KDE1DHOSymbetaKernel.hh

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#ifndef NPSTAT_KDE1DHOSYMBETAKERNEL_HH_
#define NPSTAT_KDE1DHOSYMBETAKERNEL_HH_
 
/*!
// \file KDE1DHOSymbetaKernel.hh
//
// \brief High order Gaussian or symmetric beta KDE kernels
//
// Author: I. Volobouev
//
// November 2018
*/
 
#include <vector>
 
#include "npstat/stat/AbsKDE1DKernel.hh"
#include "npstat/nm/AbsClassicalOrthoPoly1D.hh"
 
namespace npstat {
    class KDE1DHOSymbetaKernel : public AbsKDE1DKernel
    {
    public:
        // Use power < 0 for Gaussian. Kernel order will be
        // "filterDegree" +  2 if "filterDegree" is even,
        // and "filterDegree" + 1 if "filterDegree" is odd.
        KDE1DHOSymbetaKernel(int power, double filterDegree, double normfactor=1.0);
 
        KDE1DHOSymbetaKernel(const KDE1DHOSymbetaKernel& r);
        KDE1DHOSymbetaKernel& operator=(const KDE1DHOSymbetaKernel& r);
 
        inline virtual KDE1DHOSymbetaKernel* clone() const
            {return new KDE1DHOSymbetaKernel(*this);}
 
        inline virtual ~KDE1DHOSymbetaKernel() {delete poly_;}
 
        virtual void setNormFactor(double normfactor);
 
        inline int power() const {return power_;}
        inline double filterDegree() const {return filterDegree_;}
        inline double weight(const double x) const {return poly_->weight(x);}
 
        inline double xmin() const {return xmin_;}
        inline double xmax() const {return xmax_;}
        inline double normFactor() const {return norm_;}
 
        double operator()(const double x) const;
 
    private:
        void copyInternals(const KDE1DHOSymbetaKernel& r);
 
        int power_;
        unsigned maxdeg_;
        double filterDegree_;
        double xmin_;
        double xmax_;
        double lastShrinkage_;
        double norm_;
        AbsClassicalOrthoPoly1D* poly_;
        mutable std::vector<long double> polyValues_;
    };
}
 
#endif // NPSTAT_KDE1DHOSYMBETAKERNEL_HH_