Lreg Class Reference

Class for linear parameteric regression. More...

#include <lreg.h>

Inheritance diagram for Lreg:

Public Member Functions
	Lreg ()
	Constructor.
	~Lreg ()
	Destrcutor.
virtual void	SetMindex (Array2D< int > &mindex)
	Set multiindex.
virtual void	GetMindex (Array2D< int > &mindex)
	Get multiindex.
virtual void	SetCenters (Array2D< double > &centers)
	Set centers (for RBF)
virtual void	SetWidths (Array1D< double > &widths)
	Set widths (for RBF)
virtual void	SetParamsRBF ()
	Set parameters (for RBF)
virtual void	EvalBases (Array2D< double > &xx, Array2D< double > &bb)
	Evaluate bases.
virtual void	StripBases (Array1D< int > &used)
	Strip bases.
void	InitRegr ()
	Initialize.
void	SetupData (Array2D< double > &xdata, Array1D< double > &ydata)
	Setup data (1d ydata)
void	SetupData (Array2D< double > &xdata, Array2D< double > &ydata)
	Setup data (2d ydata)
void	SetRegMode (string regmode)
	Set the regression mode.
void	SetRegWeights (Array1D< double > &weights)
	Set weights.
void	BCS_BuildRegr (Array1D< int > &selected, double eta)
	Build BCS regression.
void	LSQ_BuildRegr ()
	Build LSQ regression.
void	EvalRegr (Array2D< double > &xcheck, Array1D< double > &ycheck, Array1D< double > &yvar, Array2D< double > &ycov)
	Evaluate the regression expansion.
int	GetNpt () const
	Get the number of points.
int	GetNdim () const
	Get dimensionality.
int	GetNbas () const
	Get the number of bases.
double	GetSigma2 () const
	Get the variance of the data.
void	GetCoefCov (Array2D< double > &coef_cov)
	Get coefficient covariance.
void	GetCoef (Array1D< double > &coef)
	Get coefficients.
void	Proj (Array1D< double > &array, Array1D< double > &proj_array)
	Project.
Array1D< double >	LSQ_computeBestLambdas ()
	Compute the best values for regulariation parameter vector lambda, for LSQ.
double	LSQ_computeBestLambda ()
	Compute the best value for regulariation parameter lambda, for LSQ.
void	getResid ()
	Compute the residual vector, if not already computed.
void	getDiagP ()
	Compute the diagonal of projection matrix, if not already computed.
Array1D< double >	computeErrorMetrics (string method)
	Compote error according to a selected metrics.
double	computeRVE (Array2D< double > &xval, Array1D< double > &yval, Array1D< double > &yval_regr)
	Compute validation error.

Protected Attributes
Array2D< double >	xdata_
	xdata array
Array1D< double >	ydata_
	ydata array
int	npt_
	Number of samples.
int	nbas_
	Number of bases.
int	ndim_
	Dimensionality.
Array1D< double >	sigma2_
	Variance.
Array1D< double >	weights_
	Weights.
Array1D< double >	resid_
	Residuals.
bool	residFlag_
	Flag to indicate whether residual is computed.
Array1D< double >	diagP_
	Diagonal of projection matrix.
bool	diagPFlag_
	Flag to indicate whether diagonal of projetion matrix is computed.
Array2D< double >	bdata_
	Auxiliary matrix or vector; see UQTk Manual.
Array2D< double >	A_
Array2D< double >	A_inv_
Array2D< double >	coef_cov_
Array1D< double >	Hty_
Array1D< double >	coef_
Array1D< double >	coef_erb_

Private Member Functions
double	LSQ_computeLOO ()
	Compute Leave-one-out error for LSQ.
double	LSQ_computeGCV ()
	COmpute generalized-cross-validation error for LSQ.

Private Attributes
bool	dataSetFlag_
	Flag to indicate whether data has been set or not.
string	regMode_
	Regression mode (m, ms, msc for mean-only, mean+variance, mean+covariance)

Detailed Description

Class for linear parameteric regression.

Constructor & Destructor Documentation

Lreg()

Lreg::Lreg ( )

inline

Constructor.

~Lreg()

Lreg::~Lreg ( )

inline

Destrcutor.

Member Function Documentation

BCS_BuildRegr()

void Lreg::BCS_BuildRegr	(	Array1D< int > &	selected,
		double	eta )

Build BCS regression.

computeErrorMetrics()

Array1D< double > Lreg::computeErrorMetrics

(

string

method

)

Compote error according to a selected metrics.

computeRVE()

double Lreg::computeRVE	(	Array2D< double > &	xval,
		Array1D< double > &	yval,
		Array1D< double > &	yval_regr )

Compute validation error.

EvalBases()

virtual void Lreg::EvalBases ( Array2D< double > & xx, Array2D< double > & bb )

inlinevirtual

Evaluate bases.

Reimplemented in PCreg, PLreg, and RBFreg.

EvalRegr()

void Lreg::EvalRegr	(	Array2D< double > &	xcheck,
		Array1D< double > &	ycheck,
		Array1D< double > &	yvar,
		Array2D< double > &	ycov )

Evaluate the regression expansion.

GetCoef()

void Lreg::GetCoef ( Array1D< double > & coef )

inline

Get coefficients.

GetCoefCov()

void Lreg::GetCoefCov ( Array2D< double > & coef_cov )

inline

Get coefficient covariance.

getDiagP()

void Lreg::getDiagP

(

)

Compute the diagonal of projection matrix, if not already computed.

GetMindex()

virtual void Lreg::GetMindex ( Array2D< int > & mindex )

inlinevirtual

Get multiindex.

Reimplemented in PCreg, and PLreg.

GetNbas()

int Lreg::GetNbas ( ) const

inline

Get the number of bases.

GetNdim()

int Lreg::GetNdim ( ) const

inline

Get dimensionality.

GetNpt()

int Lreg::GetNpt ( ) const

inline

Get the number of points.

getResid()

void Lreg::getResid

(

)

Compute the residual vector, if not already computed.

GetSigma2()

double Lreg::GetSigma2 ( ) const

inline

Get the variance of the data.

InitRegr()

void Lreg::InitRegr

(

)

Initialize.

LSQ_BuildRegr()

void Lreg::LSQ_BuildRegr

(

)

Build LSQ regression.

LSQ_computeBestLambda()

double Lreg::LSQ_computeBestLambda

(

)

Compute the best value for regulariation parameter lambda, for LSQ.

LSQ_computeBestLambdas()

Array1D< double > Lreg::LSQ_computeBestLambdas

(

)

Compute the best values for regulariation parameter vector lambda, for LSQ.

LSQ_computeGCV()

double Lreg::LSQ_computeGCV ( )

private

COmpute generalized-cross-validation error for LSQ.

LSQ_computeLOO()

double Lreg::LSQ_computeLOO ( )

private

Compute Leave-one-out error for LSQ.

Proj()

void Lreg::Proj	(	Array1D< double > &	array,
		Array1D< double > &	proj_array )

Project.

SetCenters()

virtual void Lreg::SetCenters ( Array2D< double > & centers )

inlinevirtual

Set centers (for RBF)

Reimplemented in RBFreg.

SetMindex()

virtual void Lreg::SetMindex ( Array2D< int > & mindex )

inlinevirtual

Set multiindex.

Reimplemented in PCreg, and PLreg.

SetParamsRBF()

virtual void Lreg::SetParamsRBF ( )

inlinevirtual

Set parameters (for RBF)

SetRegMode()

void Lreg::SetRegMode ( string regmode )

inline

Set the regression mode.

SetRegWeights()

void Lreg::SetRegWeights

(

Array1D< double > &

weights

)

Set weights.

SetupData() [1/2]

void Lreg::SetupData	(	Array2D< double > &	xdata,
		Array1D< double > &	ydata )

Setup data (1d ydata)

SetupData() [2/2]

void Lreg::SetupData	(	Array2D< double > &	xdata,
		Array2D< double > &	ydata )

Setup data (2d ydata)

SetWidths()

virtual void Lreg::SetWidths ( Array1D< double > & widths )

inlinevirtual

Set widths (for RBF)

Reimplemented in RBFreg.

StripBases()

virtual void Lreg::StripBases ( Array1D< int > & used )

inlinevirtual

Strip bases.

Reimplemented in PCreg, PLreg, and RBFreg.

Member Data Documentation

A_

Array2D<double> Lreg::A_

protected

A_inv_

Array2D<double> Lreg::A_inv_

protected

bdata_

Array2D<double> Lreg::bdata_

protected

Auxiliary matrix or vector; see UQTk Manual.

coef_

Array1D<double> Lreg::coef_

protected

coef_cov_

Array2D<double> Lreg::coef_cov_

protected

coef_erb_

Array1D<double> Lreg::coef_erb_

protected

dataSetFlag_

bool Lreg::dataSetFlag_

private

Flag to indicate whether data has been set or not.

diagP_

Array1D<double> Lreg::diagP_

protected

Diagonal of projection matrix.

diagPFlag_

bool Lreg::diagPFlag_

protected

Flag to indicate whether diagonal of projetion matrix is computed.

Hty_

Array1D<double> Lreg::Hty_

protected

nbas_

int Lreg::nbas_

protected

Number of bases.

ndim_

int Lreg::ndim_

protected

Dimensionality.

npt_

int Lreg::npt_

protected

Number of samples.

regMode_

string Lreg::regMode_

private

Regression mode (m, ms, msc for mean-only, mean+variance, mean+covariance)

resid_

Array1D<double> Lreg::resid_

protected

Residuals.

residFlag_

bool Lreg::residFlag_

protected

Flag to indicate whether residual is computed.

sigma2_

Array1D<double> Lreg::sigma2_

protected

Variance.

weights_

Array1D<double> Lreg::weights_

protected

Weights.

xdata_

Array2D<double> Lreg::xdata_

protected

xdata array

ydata_

Array1D<double> Lreg::ydata_

protected

ydata array

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The documentation for this class was generated from the following files:

• lreg.h
• lreg.cpp