theplu::yat::regression::MultiDimensional Class Reference

Linear MultiDimesional regression. More...

#include <yat/regression/MultiDimensional.h>

Inheritance diagram for theplu::yat::regression::MultiDimensional:

Public Member Functions
	MultiDimensional (void)
	Default Constructor.
	~MultiDimensional (void)
	Destructor.
const utility::Matrix &	covariance (void) const
	covariance of parameters More...
void	fit2 (const utility::MatrixBase &X, const utility::VectorBase &y)
	Function fitting parameters of the linear model by miminizing the quadratic deviation between model and data. More...
void	fit (const utility::Matrix &X, const utility::VectorBase &y)
const utility::Vector &	fit_parameters (void) const
double	chisq (void) const
	Summed Squared Error.
double	predict (const utility::VectorBase &x) const
double	prediction_error2 (const utility::VectorBase &x) const
double	standard_error2 (const utility::VectorBase &x) const

Detailed Description

Linear MultiDimesional regression.

Member Function Documentation

covariance()

const utility::Matrix& theplu::yat::regression::MultiDimensional::covariance

(

void

)

const

covariance of parameters

The covariance of fit parameters is calculated as where is the variance of error residuals.

fit()

void theplu::yat::regression::MultiDimensional::fit ( const utility::Matrix &  X, const utility::VectorBase &  y  )

virtual

Just kept for back compatibility with yat 0.19. Exactly the same behaviour as for fit2.

Implements theplu::yat::regression::Multivariate.

fit2()

void theplu::yat::regression::MultiDimensional::fit2 ( const utility::MatrixBase &  X, const utility::VectorBase &  y  )

virtual

Function fitting parameters of the linear model by miminizing the quadratic deviation between model and data.

Number of rows in X must match size of y.

Exceptions

A	GSL_error exception is thrown if memory allocation fails or the underlying GSL calls fails (usually matrix dimension errors).

Since

New in yat 0.20

Reimplemented from theplu::yat::regression::Multivariate.

fit_parameters()

const utility::Vector& theplu::yat::regression::MultiDimensional::fit_parameters ( void  ) const

virtual

Returns

parameters of the model

Implements theplu::yat::regression::Multivariate.

predict()

double theplu::yat::regression::MultiDimensional::predict ( const utility::VectorBase &  x ) const

virtual

Returns

value in x according to fitted model

Implements theplu::yat::regression::Multivariate.

prediction_error2()

double theplu::yat::regression::MultiDimensional::prediction_error2

(

const utility::VectorBase &

x

)

const

Returns

expected squared prediction error for a new data point in x

standard_error2()

double theplu::yat::regression::MultiDimensional::standard_error2

(

const utility::VectorBase &

x

)

const

Returns

squared error of model value in x

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

• yat/regression/MultiDimensional.h