AdaptiveKernelDensityEstimation.h

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// SPDX-FileCopyrightText: The Bio++ Development Group
//
// SPDX-License-Identifier: CECILL-2.1

#ifndef BPP_NUMERIC_ADAPTIVEKERNELDENSITYESTIMATION_H
#define BPP_NUMERIC_ADAPTIVEKERNELDENSITYESTIMATION_H


#include "Matrix/Matrix.h"

namespace bpp
{
class AdaptiveKernelDensityEstimation
{
private:
  RowMatrix<double> x_; // The original sample
  size_t n_;
  size_t r_;
  RowMatrix<double> covar_; // The covariance matrix, used for the linear transformation
  RowMatrix<double> invSqrtCovar_; // The inverse of the square root of the covariance matrix, used for the linear transformation
  std::vector<double> xMean_;
  double gamma_; // Tune the effect of the pilot density.
  double c1_;
  std::vector<double> c2_;
  double h_; // The bandwidth.
  std::vector<double> lambda_; // The local tuning coefficient of the bandwidth.
  std::vector<double> pilot_; // The pilot density

public:
  AdaptiveKernelDensityEstimation(const Matrix<double>& x, double gamma = 0.5) :
    x_(x), n_(x.getNumberOfColumns()), r_(x.getNumberOfRows()),
    covar_(), invSqrtCovar_(), xMean_(), gamma_(gamma),
    c1_(0), c2_(x.getNumberOfColumns()), h_(0),
    lambda_(x.getNumberOfColumns()), pilot_(x.getNumberOfColumns())
  {
    init_();
  }
  virtual ~AdaptiveKernelDensityEstimation() {}

public:
  double kDensity(const std::vector<double>& x);

private:
  void init_();

  void sampleMean_(const Matrix<double>& x, std::vector<double>& mean);

  double kernel_(const Matrix<double>& x);
};
} // End of namespace bpp.
#endif // BPP_NUMERIC_ADAPTIVEKERNELDENSITYESTIMATION_H