lr_adf Class Reference

Class for wrapping Eigen objects into Armadillo ones to perform linear regression. More...

#include <ADF_lr.hpp>

Public Member Functions
template<typename STOR_OBJ1, typename STOR_OBJ2>
	lr_adf (STOR_OBJ1 &&x, STOR_OBJ2 &&y)
	Class constructor.
void	std_er_coeff (const arma::mat &x)
	Standard errors in the estimate of the coefficients: modifying m_se_coeff.
void	solve ()
	Fitting the linear regression, retaining coeffiecients and standard errors on their estimate.
KO_Traits::StoringVector	coeff () const
	Getter for the linear regression coefficients.
KO_Traits::StoringVector	se_coeff () const
	Getter for the linear regression standard errors on the coefficients.

Detailed Description

Class for wrapping Eigen objects into Armadillo ones to perform linear regression.

Template Parameters

LAG_policy

indicates if lag orders bigger than one has to be taken into account while computing the test statistic

Constructor & Destructor Documentation

lr_adf()

template<typename STOR_OBJ1, typename STOR_OBJ2>

lr_adf::lr_adf ( STOR_OBJ1 && x, STOR_OBJ2 && y )

inline

Class constructor.

Parameters

x	covariates, stored as column-wise
y	responses

covariates are transposes in the construction phases, to be coherent with mlpack

Note

Universal constructor: move semantic used to optimazing handling big size objects

Member Function Documentation

coeff()

KO_Traits::StoringVector lr_adf::coeff ( ) const

inline

Getter for the linear regression coefficients.

Returns

the private m_coeff

se_coeff()

KO_Traits::StoringVector lr_adf::se_coeff ( ) const

inline

Getter for the linear regression standard errors on the coefficients.

Returns

the private m_se_coeff

std_er_coeff()

void lr_adf::std_er_coeff ( const arma::mat & x )

inline

Standard errors in the estimate of the coefficients: modifying m_se_coeff.

Parameters

x	covariates (stored row-wise)

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

• src/ADF_lr.hpp