ols.h File Reference

Ordinary Least Squares (OLS) regression functionality. More...

#include <Eigen/Dense>
#include <Eigen/SparseCore>
#include <utility>

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Functions
std::pair< double, Eigen::VectorXd >	fitOls (const Eigen::MatrixXd &X, const Eigen::VectorXd &y, bool fit_intercept=true)
	Fits an OLS regression model using dense matrices.
std::pair< double, Eigen::VectorXd >	fitOls (const Eigen::SparseMatrix< double > &X, const Eigen::VectorXd &y, bool fit_intercept=true)
	Fits an OLS regression model using sparse matrices.

Detailed Description

Ordinary Least Squares (OLS) regression functionality.

This header provides functions for fitting Ordinary Least Squares regression models using both dense and sparse matrix representations.

Definition in file ols.h.

Function Documentation

fitOls() [1/2]

std::pair< double, Eigen::VectorXd > fitOls	(	const Eigen::MatrixXd &	X,
		const Eigen::VectorXd &	y,
		bool	fit_intercept = true
	)

Fits an OLS regression model using dense matrices.

Parameters

X	The design matrix with predictors (features) - dense representation
y	The target/response vector
fit_intercept	Whether to include an intercept term (default: true)

Returns

std::pair containing:

• double: Intercept term (or 0 if fit_intercept is false)
• Eigen::VectorXd: Coefficient vector

Definition at line 7 of file ols.cpp.

fitOls() [2/2]

std::pair< double, Eigen::VectorXd > fitOls	(	const Eigen::SparseMatrix< double > &	X,
		const Eigen::VectorXd &	y,
		bool	fit_intercept = true
	)

Fits an OLS regression model using sparse matrices.

Parameters

X	The design matrix with predictors (features) - sparse representation
y	The target/response vector
fit_intercept	Whether to include an intercept term (default: true)

Returns

std::pair containing:

• double: Intercept term (or 0 if fit_intercept is false)
• Eigen::VectorXd: Coefficient vector

Definition at line 36 of file ols.cpp.