LFit Struct Reference

Linear regression calculator using least squares method. More...

#include <lfit.H>

Public Member Functions
	LFit () noexcept
	Default constructor creates an identity fit (y = x)
	LFit (const Array< double > &x, const Array< double > &y)
	Construct and compute linear regression.
std::pair< double, double >	predict (double x) const noexcept
	Predict y-value and error for given x.

Public Attributes
double	c = 0
	Y-intercept of fitted line.
double	m = 1
	Slope of fitted line.
double	cov00 = 0
	Covariance matrix element (0,0)
double	cov01 = 0
	Covariance matrix element (0,1)
double	cov11 = 0
	Covariance matrix element (1,1)
double	sumsq = 0
	Sum of squared residuals.
double	r2 = 0
	Coefficient of determination.
double	sigma = 0
	Standard deviation of errors.
double	mse = 0
	Mean squared error.

Friends
std::ostream &	operator<< (std::ostream &out, const LFit &f)
	Output stream operator for fit results.

Detailed Description

Linear regression calculator using least squares method.

Computes the best-fit line y = c + m*x that minimizes the sum of squared residuals. Uses GSL for numerical computation.

Computed Statistics

Field	Description
c	Y-intercept
m	Slope
r2	Coefficient of determination (0-1)
sumsq	Sum of squared residuals
sigma	Standard deviation of errors
mse	Mean squared error

Definition at line 98 of file lfit.H.

Constructor & Destructor Documentation

LFit() [1/2]

LFit::LFit ( )

inlinenoexcept

Default constructor creates an identity fit (y = x)

Definition at line 128 of file lfit.H.

LFit() [2/2]

LFit::LFit ( const Array< double > &  x, const Array< double > &  y  )

inline

Construct and compute linear regression.

Fits the model y = c + m*x to minimize sum of squared errors. Computes R², standard deviation, and MSE.

Parameters

x	Array of independent variable values
y	Array of dependent variable values

Exceptions

SizeMismatch	if x and y have different sizes
SizeMismatch	if arrays have only 1 element

Example

Array<double> x = {1, 2, 3, 4};
Array<double> y = {2, 4, 6, 8};
LFit fit(x, y);  // Perfect fit: y = 2x, R² = 1.0

Definition at line 149 of file lfit.H.

References ALEPHTHROW, Aleph::Array< T >::base(), c, cov00, cov01, cov11, Aleph::diff(), Aleph::error(), Aleph::is_normal_number(), m, Aleph::maps(), mse, Aleph::pow2(), r2, sigma, Aleph::Array< T >::size(), sqrt(), sumsq, y, and Aleph::zip_it().

Member Function Documentation

predict()

std::pair< double, double > LFit::predict ( double  x ) const

inlinenoexcept

Predict y-value and error for given x.

Uses the fitted model to predict y at the given x value, along with an error estimate based on the covariance matrix.

Parameters

x	Independent variable value

Returns

Pair (predicted_y, error_estimate)

Example

LFit fit(x_data, y_data);
auto [y, err] = fit.predict(10.0);
// y ± err is the predicted range

Definition at line 202 of file lfit.H.

References c, cov00, cov01, cov11, m, Aleph::maps(), and y.

Friends And Related Symbol Documentation

operator<<

std::ostream & operator<< ( std::ostream &  out, const LFit &  f  )

friend

Output stream operator for fit results.

Parameters

out	Output stream
f	LFit object to output

Returns

Reference to output stream

Definition at line 117 of file lfit.H.

Member Data Documentation

c

double LFit::c = 0

mutable

Y-intercept of fitted line.

Definition at line 100 of file lfit.H.

Referenced by LFit(), and predict().

cov00

double LFit::cov00 = 0

mutable

Covariance matrix element (0,0)

Definition at line 102 of file lfit.H.

Referenced by LFit(), and predict().

cov01

double LFit::cov01 = 0

mutable

Covariance matrix element (0,1)

Definition at line 103 of file lfit.H.

Referenced by LFit(), and predict().

cov11

double LFit::cov11 = 0

mutable

Covariance matrix element (1,1)

Definition at line 104 of file lfit.H.

Referenced by LFit(), and predict().

m

double LFit::m = 1

mutable

Slope of fitted line.

Definition at line 101 of file lfit.H.

Referenced by LFit(), and predict().

mse

double LFit::mse = 0

mutable

Mean squared error.

Definition at line 108 of file lfit.H.

Referenced by LFit().

r2

double LFit::r2 = 0

mutable

Coefficient of determination.

Definition at line 106 of file lfit.H.

Referenced by LFit().

sigma

double LFit::sigma = 0

mutable

Standard deviation of errors.

Definition at line 107 of file lfit.H.

Referenced by LFit().

sumsq

double LFit::sumsq = 0

mutable

Sum of squared residuals.

Definition at line 105 of file lfit.H.

Referenced by LFit().

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

• lfit.H