This is the class used to fit a log linear regression line to compare 2 vectors. More...

#include <regressionline.h>

Inheritance diagram for LogLinearRegression:

Collaboration diagram for LogLinearRegression:

Public Member Functions
	LogLinearRegression (LineType ltype)
	This is the default LogLinearRegression constructor. More...

	~LogLinearRegression ()
	This is the default LogLinearRegression destructor. More...

virtual void	storeVectors (const DoubleVector &modData, const DoubleVector &obsData)
	This is the function that stores 2 vectors that will be compared using a log linear regression line. More...

Public Member Functions inherited from Regression
	Regression ()
	This is the default Regression constructor. More...

	Regression (LineType ltype)
	This is the Regression constructor for a regression line of a specified LineType. More...

virtual	~Regression ()
	This is the default Regression destructor. More...

void	calcFit ()
	This is the function that fits a regression line to compare the 2 vectors that have been stored, according to the LineType that has been defined. More...

void	setIntercept (double intercept)
	This function will set the intercept of the regression line. More...

void	setSlope (double slope)
	This function will set the slope of the regression line. More...

void	setWeights (const DoubleVector &weights)
	This function will set the weights that can be used to fit the regression line. More...

int	getError ()
	This function will check to see if an error has occured. More...

double	getSSE ()
	This function will return the sum of squares of errors calculated when fitting the regression line. More...

double	getIntercept ()
	This function will return the intercept of the regression line. More...

double	getSlope ()
	This function will return the slope of the regression line. More...

LineType	getType () const
	This function will return the fit type for the regression line. More...

Additional Inherited Members
Protected Member Functions inherited from Regression
void	calcSSE ()
	This function will calculate the sum of squares of errors for the regession line. More...

void	calcSSEWeights ()
	This function will calculate the weighted sum of squares of errors for the regession line. More...

void	calcSlope ()
	This function will calculate the slope of the regession line. More...

void	calcIntercept ()
	This function will calculate the intercept of the regession line. More...

void	calcSlopeIntercept ()
	This function will calculate both the slope and the intercept of the regession line. More...

Protected Attributes inherited from Regression
int	error
	This is the flag to denote whether an error has occured. More...

int	useweights
	This is the flag to denote whether the weights should be used when calculating the fit to the regression line. More...

double	sse
	This is the sum of squares of errors from the regression line. More...

double	a
	This is the intercept of the regression line. More...

double	b
	This is the slope of the regression line. More...

DoubleVector	w
	This is the DoubleVector of weights that can be used to fit the regression line. More...

DoubleVector	x
	This is the DoubleVector that will contain the the modelled data to be used to fit the regression line. More...

DoubleVector	y
	This is the DoubleVector that will contain the the observed data to be used to fit the regression line. More...

LineType	linetype
	This denotes what type of line fit is to be used for the regression line. More...

Detailed Description

This is the class used to fit a log linear regression line to compare 2 vectors.

Constructor & Destructor Documentation

◆ LogLinearRegression()

LogLinearRegression::LogLinearRegression ( LineType ltype )

This is the default LogLinearRegression constructor.

Parameters

ltype is the LineType of the regression line

◆ ~LogLinearRegression()

LogLinearRegression::~LogLinearRegression ( )

inline

This is the default LogLinearRegression destructor.

Member Function Documentation

◆ storeVectors()

void LogLinearRegression::storeVectors	(	const DoubleVector &	modData,
		const DoubleVector &	obsData
	)

virtual

This is the function that stores 2 vectors that will be compared using a log linear regression line.

Parameters

modData	is the DoubleVector containing the modelled data
obsData	is the DoubleVector containing the observed data

Implements Regression.

Reimplemented in LogWeightRegression.

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

src/include/regressionline.h
src/regressionline.cc