LinearRegressionWithoutIntercept Class Reference

This class offers functions to perform least-squares fits to a straight line model, \( Y(c,x) = c_0 + c_1 x \). More...

#include <OpenMS/ML/REGRESSION/LinearRegressionWithoutIntercept.h>

Collaboration diagram for LinearRegressionWithoutIntercept:

Public Member Functions
	LinearRegressionWithoutIntercept ()
	Constructor.
void	addData (double x, double y)
	adds an observation (x,y) to the regression data set.
void	addData (std::vector< double > &x, std::vector< double > &y)
	adds observations (x,y) to the regression data set.
double	getSlope () const
	returns the slope of the estimated regression line.

Private Attributes
double	sum_xx_
	total variation in x
double	sum_xy_
	sum of products
int	n_
	number of observations

Detailed Description

This class offers functions to perform least-squares fits to a straight line model, \( Y(c,x) = c_0 + c_1 x \).

Constructor & Destructor Documentation

LinearRegressionWithoutIntercept()

LinearRegressionWithoutIntercept

(

)

Constructor.

Member Function Documentation

addData() [1/2]

void addData	(	double	x,
		double	y
	)

adds an observation (x,y) to the regression data set.

Parameters

[in]	x	independent variable value
[in]	y	dependent variable value

addData() [2/2]

void addData	(	std::vector< double > &	x,
		std::vector< double > &	y
	)

adds observations (x,y) to the regression data set.

Parameters

[in]	x	vector of independent variable values
[in]	y	vector of dependent variable values

getSlope()

double getSlope

(

)

const

returns the slope of the estimated regression line.

Member Data Documentation

n_

int n_

private

number of observations

sum_xx_

double sum_xx_

private

total variation in x

sum_xy_

double sum_xy_

private

sum of products