linear_regression.hpp File Reference

Linear regression analysis. More...

#include "statcpp/basic_statistics.hpp"
#include "statcpp/continuous_distributions.hpp"
#include "statcpp/correlation_covariance.hpp"
#include <cmath>
#include <cstddef>
#include <limits>
#include <stdexcept>
#include <string>
#include <vector>

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Classes
struct	statcpp::simple_regression_result
	Structure to store simple regression analysis results. More...
struct	statcpp::multiple_regression_result
	Structure to store multiple regression analysis results. More...
struct	statcpp::prediction_interval
	Structure to store prediction interval results. More...
struct	statcpp::residual_diagnostics
	Structure to store residual diagnostics results. More...

Namespaces
namespace	statcpp
namespace	statcpp::detail
	Internal helper functions.

Functions
template<typename IteratorX , typename IteratorY >
simple_regression_result	statcpp::simple_linear_regression (IteratorX x_first, IteratorX x_last, IteratorY y_first, IteratorY y_last)
	Perform simple linear regression.
void	statcpp::detail::validate_matrix_structure (const std::vector< std::vector< double > > &data, const char *func_name)
	Validate 2D matrix structure.
void	statcpp::detail::validate_no_intercept_column (const std::vector< std::vector< double > > &X, const char *func_name)
	Check that X data does not contain an intercept column.
std::vector< std::vector< double > >	statcpp::detail::transpose (const std::vector< std::vector< double > > &A)
	Calculate transpose matrix.
std::vector< std::vector< double > >	statcpp::detail::matrix_multiply (const std::vector< std::vector< double > > &A, const std::vector< std::vector< double > > &B)
	Calculate matrix product.
std::vector< double >	statcpp::detail::matrix_vector_multiply (const std::vector< std::vector< double > > &A, const std::vector< double > &v)
	Calculate matrix-vector product.
std::vector< std::vector< double > >	statcpp::detail::cholesky (const std::vector< std::vector< double > > &A)
	Perform Cholesky decomposition.
std::vector< double >	statcpp::detail::solve_cholesky (const std::vector< std::vector< double > > &L, const std::vector< double > &b)
	Solve system of equations using Cholesky decomposition.
std::vector< std::vector< double > >	statcpp::detail::inverse_cholesky (const std::vector< std::vector< double > > &L)
	Calculate inverse matrix using Cholesky decomposition.
multiple_regression_result	statcpp::multiple_linear_regression (const std::vector< std::vector< double > > &X, const std::vector< double > &y)
	Perform multiple linear regression.
double	statcpp::predict (const simple_regression_result &model, double x)
	Make prediction using simple regression model.
double	statcpp::predict (const multiple_regression_result &model, const std::vector< double > &x)
	Make prediction using multiple regression model.
template<typename IteratorX >
prediction_interval	statcpp::prediction_interval_simple (const simple_regression_result &model, IteratorX x_first, IteratorX x_last, double x_new, double confidence=0.95)
	Calculate prediction interval for simple regression model.
template<typename IteratorX >
prediction_interval	statcpp::confidence_interval_mean (const simple_regression_result &model, IteratorX x_first, IteratorX x_last, double x_new, double confidence=0.95)
	Calculate confidence interval for mean of simple regression model.
template<typename IteratorX , typename IteratorY >
residual_diagnostics	statcpp::compute_residual_diagnostics (const simple_regression_result &model, IteratorX x_first, IteratorX x_last, IteratorY y_first, IteratorY y_last)
	Perform residual diagnostics for simple regression model.
residual_diagnostics	statcpp::compute_residual_diagnostics (const multiple_regression_result &model, const std::vector< std::vector< double > > &X, const std::vector< double > &y)
	Perform residual diagnostics for multiple regression model.
std::vector< double >	statcpp::compute_vif (const std::vector< std::vector< double > > &X)
	Calculate VIF (Variance Inflation Factor) for each predictor.
double	statcpp::correlation_matrix_determinant (const std::vector< std::vector< double > > &X)
	Calculate determinant of correlation matrix.
double	statcpp::multicollinearity_score (const std::vector< std::vector< double > > &X)
	Calculate multicollinearity score.
template<typename IteratorY , typename IteratorPred >
double	statcpp::r_squared (IteratorY y_first, IteratorY y_last, IteratorPred pred_first, IteratorPred pred_last)
	Calculate coefficient of determination from observed and predicted values.
template<typename IteratorY , typename IteratorPred >
double	statcpp::adjusted_r_squared (IteratorY y_first, IteratorY y_last, IteratorPred pred_first, IteratorPred pred_last, std::size_t num_predictors)
	Calculate adjusted coefficient of determination.

Detailed Description

Linear regression analysis.

Provides linear regression analysis functionality including simple regression, multiple regression, and polynomial regression. Includes prediction, confidence intervals, residual diagnostics, and multicollinearity diagnostics.

Definition in file linear_regression.hpp.