theoretica::regression Namespace Reference

Regression to a model. More...

Classes
class	linear_model
	structure for computation and storage of least squares linear regression results with model \(y = A + Bx\). More...

Functions
template<typename Dataset1 , typename Dataset2 >
void	ols_linear (const Dataset1 &X, const Dataset2 &Y, real &intercept, real &slope)
	Compute the coefficients of the linear regression using Ordinary Least Squares.
template<typename Dataset1 , typename Dataset2 >
void	ols_linear (const Dataset1 &X, const Dataset2 &Y, real sigma_Y, real &intercept, real &slope, real &sigma_A, real &sigma_B)
	Compute the coefficients of the linear regression using Ordinary Least Squares.
template<typename Dataset1 , typename Dataset2 >
void	ols_linear (const Dataset1 &X, const Dataset2 &Y, real sigma_Y, real &intercept, real &slope, mat2 &covar_mat)
	Compute the coefficients of the linear regression using Ordinary Least Squares.
template<typename Dataset1 , typename Dataset2 , typename Dataset3 >
void	wls_linear (const Dataset1 &X, const Dataset2 &Y, const Dataset3 &W, real &intercept, real &slope, mat2 &covar_mat)
	Compute the coefficients of the linear regression using Weighted Least Squares.
template<typename Dataset1 , typename Dataset2 >
void	wls_linear (const Dataset1 &X, const Dataset2 &Y, real sigma_X, real sigma_Y, real &intercept, real &slope, mat2 &covar_mat)
	Compute the coefficients of the linear regression using Weighted Least Squares.
template<typename Dataset1 , typename Dataset2 >
void	ols_linear_orig (const Dataset1 &X, const Dataset2 &Y, real sigma_Y, real &B, real &sigma_B)
	Compute the Ordinary Least Squares regression to a line passing through the origin.
template<typename Dataset1 , typename Dataset2 , typename Dataset3 >
void	wls_linear_orig (const Dataset1 &X, const Dataset2 &Y, const Dataset3 &W, real &B, real &sigma_B)
	Compute the Weight Least Squares regression to a line passing through the origin.
template<typename Dataset1 , typename Dataset2 >
real	ols_linear_error (const Dataset1 &X, const Dataset2 &Y, real intercept, real slope)
	Compute the error of the least squares linear regression from the X and Y datasets.
template<typename Dataset1 , typename Dataset2 >
real	ols_linear_intercept (const Dataset1 &X, const Dataset2 &Y)
	Compute the intercept of the least squares linear regression from X and Y.
template<typename Dataset1 , typename Dataset2 >
real	ols_linear_sigma_A (const Dataset1 &X, const Dataset2 &Y, real sigma_y)
	Compute the error on the intercept (A)
template<typename Dataset1 , typename Dataset2 >
real	ols_linear_slope (const Dataset1 &X, const Dataset2 &Y)
	Compute the slope of the least squares linear regression from X and Y.
template<typename Dataset1 , typename Dataset2 >
real	ols_linear_sigma_B (const Dataset1 &X, const Dataset2 &Y, real sigma_y)
	Compute the error on the slope coefficient (B)
template<typename Dataset1 , typename Dataset2 , typename Dataset3 >
real	wls_linear_intercept (const Dataset1 &X, const Dataset2 &Y, const Dataset3 &W)
	Compute the intercept of the weighted least squares linear regression from X and Y.
template<typename Dataset1 , typename Dataset2 , typename Dataset3 >
real	wls_linear_slope (const Dataset1 &X, const Dataset2 &Y, const Dataset3 &W)
	Compute the slope of the weighted least squares linear regression from X and Y.

Detailed Description

Regression to a model.