OpenMS  2.6.0
Public Member Functions | Private Attributes | List of all members
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/MATH/STATISTICS/LinearRegressionWithoutIntercept.h>

Collaboration diagram for LinearRegressionWithoutIntercept:
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Public Member Functions

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

Private Attributes

double sum_xx_
 total variation in x More...
 
double sum_xy_
 sum of products More...
 
int n_
 number of observations More...
 

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()

Constructor.

Member Function Documentation

◆ addData() [1/2]

void addData ( double  x,
double  y 
)

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

Parameters
xindependent variable value
ydependent 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
xvector of independent variable values
yvector of dependent variable values

◆ getSlope()

double getSlope ( )

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