LeastSquaresRegression Class Reference

Performs least squares regression to fit a quadratic curve to data points. More...

#include <gin_leastsquaresregression.h>

Public Member Functions
	LeastSquaresRegression ()=default
	Creates an empty regression object.
void	addPoint (double x, double y)
	Adds a data point to the regression.
void	addPoint (Point< double > point)
	Adds a data point to the regression.
void	addPoints (juce::Array< Point< double > > points)
	Adds multiple data points to the regression.
void	clear ()
	Removes all data points.
bool	enoughPoints ()
	Checks if enough points have been added for valid regression.
juce::Array< double >	getTerms ()
	Returns all three coefficients as an array.
double	aTerm ()
	Returns the coefficient of the x² term.
double	bTerm ()
	Returns the coefficient of the x term.
double	cTerm ()
	Returns the constant term.
double	rSquare ()
	Returns the coefficient of determination (R²).

Detailed Description

Performs least squares regression to fit a quadratic curve to data points.

This class fits a quadratic equation y = ax² + bx + c to a set of data points using the least squares method. It calculates the coefficients (a, b, c) that minimize the sum of squared differences between the data points and the curve.

The class also computes R² (the coefficient of determination), which measures how well the curve fits the data (values closer to 1.0 indicate better fit).

Example usage:

LeastSquaresRegression regression;
regression.addPoint (1.0, 2.5);
regression.addPoint (2.0, 5.2);
regression.addPoint (3.0, 8.8);
// ... add more points
 
if (regression.enoughPoints())
{
    double a = regression.aTerm();  // Coefficient of x²
    double b = regression.bTerm();  // Coefficient of x
    double c = regression.cTerm();  // Constant term
    double r2 = regression.rSquare();  // Goodness of fit
}

Based on code from: https://www.codeproject.com/Articles/63170/Least-Squares-Regression-for-Quadratic-Curve-Fitti

See also

aTerm, bTerm, cTerm, rSquare

Constructor & Destructor Documentation

LeastSquaresRegression()

LeastSquaresRegression::LeastSquaresRegression ( )

default

Creates an empty regression object.

Member Function Documentation

addPoint() [1/2]

void LeastSquaresRegression::addPoint	(	double	x,
		double	y
	)

Adds a data point to the regression.

Parameters

x	The x coordinate
y	The y coordinate

addPoint() [2/2]

void LeastSquaresRegression::addPoint

(

Point< double >

point

)

Adds a data point to the regression.

Parameters

point

The point to add

addPoints()

void LeastSquaresRegression::addPoints

(

juce::Array< Point< double > >

points

)

Adds multiple data points to the regression.

Parameters

points

Array of points to add

clear()

void LeastSquaresRegression::clear

(

)

Removes all data points.

enoughPoints()

bool LeastSquaresRegression::enoughPoints

(

)

Checks if enough points have been added for valid regression.

Returns

true if there are enough points to calculate the curve

getTerms()

juce::Array< double > LeastSquaresRegression::getTerms

(

)

Returns all three coefficients as an array.

Returns

Array containing [a, b, c] where y = ax² + bx + c

aTerm()

double LeastSquaresRegression::aTerm

(

)

Returns the coefficient of the x² term.

Returns

The 'a' coefficient in y = ax² + bx + c

bTerm()

double LeastSquaresRegression::bTerm

(

)

Returns the coefficient of the x term.

Returns

The 'b' coefficient in y = ax² + bx + c

cTerm()

double LeastSquaresRegression::cTerm

(

)

Returns the constant term.

Returns

The 'c' coefficient in y = ax² + bx + c

rSquare()

double LeastSquaresRegression::rSquare

(

)

Returns the coefficient of determination (R²).

R² measures how well the curve fits the data, ranging from 0 to 1. Values closer to 1 indicate a better fit.

Returns

The R² value

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

• gin_leastsquaresregression.h