37#ifndef STK_KERNELPARAMETERS_H
38#define STK_KERNELPARAMETERS_H
40#include "../STK_Clust_Util.h"
77 inline Real const&
sigma2(
int k)
const {
return sigma2_;}
79 inline Real const&
dim(
int k)
const {
return dim_[k];}
82 void updateStatistics();
86 void releaseStatistics();
97 for(
int k=dim_.begin(); k<dim_.end(); ++k)
101 sigma2_ /= dim_.size();
134 inline Real const&
dim(
int k)
const {
return dim_[k];}
137 void updateStatistics();
139 void setStatistics();
141 void releaseStatistics();
148 template<
class Array>
151 for(
int k=dim_.begin(); k<dim_.end(); ++k)
In this file we define and implement the final class Array1D.
In this file we implement the final class CArrayPoint.
This file contain the definition and implementation of the Online classes.
The MultidimRegression class allows to regress a multidimensional output variable among a multivariat...
const int baseIdx
base index of the containers created in STK++.
double Real
STK fundamental type of Real values.
The namespace STK is the main domain space of the Statistical ToolKit project.
Stat::Online< Real, Real > stat_sigma2_
sigma2 statistics
Real sigma2_
variance of the variables
Array1D< Stat::Online< Real, Real > > stat_dim_
Array of the dim statistics.
CPointX dim_
dimension of the gaussian kernel
Real const & dim(int k) const
Real const & sigma2(int k) const
void setParameters(ExprBase< Array > const ¶ms)
Set the parameters of the mixture model.
Real const & dim(int k) const
Array1D< Stat::Online< Real, Real > > stat_sigma2_
Array of the sigma2 statistics.
CPointX dim_
dimension of the gaussian kernel
Array1D< Stat::Online< Real, Real > > stat_dim_
Array of the dim statistics.
CPointX sigma2_
variance of the variables
void setParameters(ExprBase< Array > const ¶ms)
Set the parameters of the mixture model.
Real const & sigma2(int k) const
struct storing the parameters of the mixture.