Public Member Functions | Static Public Member Functions | Public Attributes
GPReg< TInput > Class Template Reference

#include <gpRegression.hpp>

List of all members.

Public Member Functions

void buildGP (bool useTargets=true)
void buildTargets ()
void evalGP (const TInput &x, double &mean, double &var)
void evalGP (const TInput &x, double &mean)
double getAvgVariance ()
double getComplexity ()
double getDataFit ()
double getDataLikelihood ()
void getDerivative (std::vector< double > *r)
double getMarginalDataLikelihood ()
void getParameters (std::vector< double > *r)
 GPReg (CovFunc< TInput > *covFunc, double sigmaNoise, GPReg< TInput > *noiseGP=NULL)
 GPReg (CovFunc< TInput > *covFunc, double *sigmaNoise, GPReg< TInput > *noiseGP=NULL)
 GPReg (GPReg< TInput > *copyFromGP)
bool minimizeGSL (unsigned maxIt)
void setDataPoints (TVector< TInput > &dataPoints, TVector< double > &dataTargets)
void setParameters (std::vector< double > *r)
void setSigmaNoise (double sigma)
 ~GPReg ()

Static Public Member Functions

static void gsl_my_df (const gsl_vector *v, void *params, gsl_vector *df)
static double gsl_my_f (const gsl_vector *v, void *params)
static void gsl_my_fdf (const gsl_vector *v, void *params, double *f, gsl_vector *df)

Public Attributes

TMatrix< double > * m_C
GPReg< TInput > * m_copyFromGP
CovFunc< TInput > * m_covFunc
TVector< TInput > * m_dataPoints
TMatrix< double > * m_iC
TVector< double > * m_iCt
GPReg< TInput > * m_noiseGP
int m_numDataPoints
double m_ownSigmaNoise
double * m_sigmaNoise
TVector< double > * m_t

Detailed Description

template<class TInput>
class GPReg< TInput >

Definition at line 18 of file gpRegression.hpp.


Constructor & Destructor Documentation

template<class TInput>
GPReg< TInput >::GPReg ( CovFunc< TInput > *  covFunc,
double  sigmaNoise,
GPReg< TInput > *  noiseGP = NULL 
)
template<class TInput>
GPReg< TInput >::GPReg ( CovFunc< TInput > *  covFunc,
double *  sigmaNoise,
GPReg< TInput > *  noiseGP = NULL 
)
template<class TInput>
GPReg< TInput >::GPReg ( GPReg< TInput > *  copyFromGP)
template<class TInput>
GPReg< TInput >::~GPReg ( )

Member Function Documentation

template<class TInput>
void GPReg< TInput >::buildGP ( bool  useTargets = true)
template<class TInput>
void GPReg< TInput >::buildTargets ( )
template<class TInput>
void GPReg< TInput >::evalGP ( const TInput &  x,
double &  mean,
double &  var 
)
template<class TInput>
void GPReg< TInput >::evalGP ( const TInput &  x,
double &  mean 
)
template<class TInput>
double GPReg< TInput >::getAvgVariance ( )
template<class TInput>
double GPReg< TInput >::getComplexity ( )
template<class TInput>
double GPReg< TInput >::getDataFit ( )
template<class TInput>
double GPReg< TInput >::getDataLikelihood ( )
template<class TInput>
void GPReg< TInput >::getDerivative ( std::vector< double > *  r)
template<class TInput>
double GPReg< TInput >::getMarginalDataLikelihood ( )
template<class TInput>
void GPReg< TInput >::getParameters ( std::vector< double > *  r)
template<class TInput>
static void GPReg< TInput >::gsl_my_df ( const gsl_vector *  v,
void *  params,
gsl_vector *  df 
) [static]
template<class TInput>
static double GPReg< TInput >::gsl_my_f ( const gsl_vector *  v,
void *  params 
) [static]
template<class TInput>
static void GPReg< TInput >::gsl_my_fdf ( const gsl_vector *  v,
void *  params,
double *  f,
gsl_vector *  df 
) [static]
template<class TInput>
bool GPReg< TInput >::minimizeGSL ( unsigned  maxIt)
template<class TInput>
void GPReg< TInput >::setDataPoints ( TVector< TInput > &  dataPoints,
TVector< double > &  dataTargets 
)
template<class TInput>
void GPReg< TInput >::setParameters ( std::vector< double > *  r)
template<class TInput>
void GPReg< TInput >::setSigmaNoise ( double  sigma)

Member Data Documentation

template<class TInput>
TMatrix<double>* GPReg< TInput >::m_C

Definition at line 58 of file gpRegression.hpp.

template<class TInput>
GPReg<TInput>* GPReg< TInput >::m_copyFromGP

Definition at line 52 of file gpRegression.hpp.

template<class TInput>
CovFunc<TInput>* GPReg< TInput >::m_covFunc

Definition at line 62 of file gpRegression.hpp.

template<class TInput>
TVector<TInput>* GPReg< TInput >::m_dataPoints

Definition at line 56 of file gpRegression.hpp.

template<class TInput>
TMatrix<double>* GPReg< TInput >::m_iC

Definition at line 60 of file gpRegression.hpp.

template<class TInput>
TVector<double>* GPReg< TInput >::m_iCt

Definition at line 61 of file gpRegression.hpp.

template<class TInput>
GPReg<TInput>* GPReg< TInput >::m_noiseGP

Definition at line 66 of file gpRegression.hpp.

template<class TInput>
int GPReg< TInput >::m_numDataPoints

Definition at line 54 of file gpRegression.hpp.

template<class TInput>
double GPReg< TInput >::m_ownSigmaNoise

Definition at line 64 of file gpRegression.hpp.

template<class TInput>
double* GPReg< TInput >::m_sigmaNoise

Definition at line 63 of file gpRegression.hpp.

template<class TInput>
TVector<double>* GPReg< TInput >::m_t

Definition at line 57 of file gpRegression.hpp.


The documentation for this class was generated from the following file:
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gaussian_process
Author(s): Maintained by Juergen Sturm
autogenerated on Wed Dec 26 2012 15:34:14