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

MultiDimesional fitting. More...

#include <yat/regression/MultiDimensional.h>

Public Member Functions
	MultiDimensional (void)
	Default Constructor.
	~MultiDimensional (void)
	Destructor.
const utility::Matrix &	covariance (void) const
	covariance of parameters
void	fit (const utility::Matrix &X, const utility::VectorBase &y)
	Function fitting parameters of the linear model by miminizing the quadratic deviation between model and data. More...
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

MultiDimesional fitting.

Member Function Documentation

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

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).

const utility::Vector& theplu::yat::regression::MultiDimensional::fit_parameters

(

void

)

const

Returns

parameters of the model

double theplu::yat::regression::MultiDimensional::predict

(

const utility::VectorBase &

x

)

const

Returns

value in x according to fitted model

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

(

const utility::VectorBase &

x

)

const

Returns

expected squared prediction error for a new data point in x

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