creativity::data::OLS Class Reference

Class for running a basic OLS regression. More...

#include <creativity/data/OLS.hpp>

Classes
struct	ftest
	The return value of fStat() More...

Public Member Functions
	OLS ()=delete
	No default constructor.
	OLS (const Equation &model)
	Constructs an OLS solver with a model. More...
	OLS (Equation &&model)
	Constructs an OLS solver, taking over the given model.
const Equation &	model () const
	Accesses the model used for this OLS object.
unsigned int	n () const
	Returns the number of observations for this OLS object.
unsigned int	k () const
	Returns the number of variables for this OLS object.
int	df () const
	Returns the degrees of freedom of the model; this is simply n() - k(). More...
void	gather ()
	Calculates and stores the final numerical values from the model. More...
void	solve ()
	Attempts to solve the model, if not already done. More...
const Eigen::VectorXd &	beta () const
	Returns the vector of coefficients (i.e. More...
const Eigen::MatrixXd &	covariance () const
	Returns the covariance estimate of the beta estimators. More...
const Eigen::VectorXd &	se () const
	Returns the standard errors (the square roots of the diagonal of covariance()) of the beta() values. More...
const Eigen::VectorXd &	tRatios () const
	Returns the t-ratios for =0 tests, i.e. More...
const Eigen::VectorXd &	pValues () const
	Returns the p-values of the t-ratios returned by tRatios() More...
const double &	s2 () const
	Returns \(s^2\), the square of the regression standard error. More...
const Eigen::VectorXd &	residuals () const
	Returns the residuals. More...
const double &	ssr () const
	Returns the sum-of-squared residuals. More...
const double &	Rsq () const
	Returns the \(R^2\) value for the regression. More...
ftest	fTest () const
	Calculates and returns the F-test of all non-constant coefficients in the model being equal to 0. More...
const Eigen::VectorXd &	y () const
	Returns the y data used to solve the model. More...
const Eigen::MatrixXd &	X () const
	Returns the X data used to solve the model. More...

Protected Member Functions
void	requireGathered () const
	Throws a std::logic_error if the model hasn't been gathered.
void	requireSolved () const
	Throws a std::logic_error if the model hasn't been solved.

Protected Attributes
Equation	model_
	The model, given during construction.
bool	gathered_ = false
	Whether gather() has been called, to populate y_ and X_.
Eigen::VectorXd	y_
	The y vector generated from the model.
Eigen::MatrixXd	X_
	The X matrix generated from the model.
bool	solved_ = false
	Whether solve() has been called, to populate the below.
Eigen::VectorXd	beta_
	The beta vector.
Eigen::MatrixXd	var_beta_
	The estimated covariance of the beta estimators.
Eigen::VectorXd	se_
	Cached standard errors.
Eigen::VectorXd	t_ratios_
	Cached t ratios.
Eigen::VectorXd	p_values_
	Cached p-values.
Eigen::VectorXd	residuals_
	Residuals.
double	ssr_ = 0
	SSR.
double	s2_ = 0
	sigma^2 estimate
double	R2_ = 0
	R^2 value.

Friends
std::ostream &	operator<< (std::ostream &os, const OLS &ols)
	Overloaded so that an OLS object can be sent to an output stream; the output consists of the model followed by the model results if the model has been solved; just the model itself if the model hasn't been solved.

Detailed Description

Class for running a basic OLS regression.

Example:

OLS mymodel(Equation(y) + 1 + x1 + x2);
mymodel.solve();
// Do something with mymodel.beta(), etc.
std::cout << mymodel << "\n";

Constructor & Destructor Documentation

OLS()

creativity::data::OLS::OLS

(

const Equation &

model

)

Constructs an OLS solver with a model.

The model object is copied.

Member Function Documentation

beta()

const Eigen::VectorXd& creativity::data::OLS::beta

(

)

const

Returns the vector of coefficients (i.e.

the beta vector) that solve the model.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

covariance()

const Eigen::MatrixXd& creativity::data::OLS::covariance

(

)

const

Returns the covariance estimate of the beta estimators.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

df()

int creativity::data::OLS::df ( ) const

inline

Returns the degrees of freedom of the model; this is simply n() - k().

Note that this can be negative, but that such a model is certainly unsolvable.

fTest()

ftest creativity::data::OLS::fTest

(

)

const

Calculates and returns the F-test of all non-constant coefficients in the model being equal to 0.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

gather()

void creativity::data::OLS::gather

(

)

Calculates and stores the final numerical values from the model.

This is called when needed by solve(), and does not typically need to be called explicitly.

Exceptions

Variable::SizeError

if the sizes of the variables in the model do not match.

pValues()

const Eigen::VectorXd& creativity::data::OLS::pValues

(

)

const

Returns the p-values of the t-ratios returned by tRatios()

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

residuals()

const Eigen::VectorXd& creativity::data::OLS::residuals

(

)

const

Returns the residuals.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

Rsq()

const double& creativity::data::OLS::Rsq

(

)

const

Returns the \(R^2\) value for the regression.

This is centered if the model contains a constant, uncentered if it does not. Note that this constant detection depends on the model's hasConstant() method; a model constructed without a constant but with a SimpleVariable that only takes on a single value will not be considered a constant for the purposes of using centering here.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

s2()

const double& creativity::data::OLS::s2

(

)

const

Returns \(s^2\), the square of the regression standard error.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

se()

const Eigen::VectorXd& creativity::data::OLS::se

(

)

const

Returns the standard errors (the square roots of the diagonal of covariance()) of the beta() values.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

solve()

void creativity::data::OLS::solve

(

)

Attempts to solve the model, if not already done.

Exceptions

RankError

if X has too few rows, or has non-full-rank columns.

ssr()

const double& creativity::data::OLS::ssr

(

)

const

Returns the sum-of-squared residuals.

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

tRatios()

const Eigen::VectorXd& creativity::data::OLS::tRatios

(

)

const

Returns the t-ratios for =0 tests, i.e.

beta().array() / se().array()

Exceptions

std::logic_error

if the model has not been solved yet by calling solve().

X()

const Eigen::MatrixXd& creativity::data::OLS::X

(

)

const

Returns the X data used to solve the model.

gather() must have been called either explicitly or by a previous call to solve().

Exceptions

std::logic_error

if neither gather() nor solve() has been called.

y()

const Eigen::VectorXd& creativity::data::OLS::y

(

)

const

Returns the y data used to solve the model.

gather() must have been called either explicitly or by a previous call to solve().

Exceptions

std::logic_error

if neither gather() nor solve() has been called.

Collaboration diagram for creativity::data::OLS:

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

• creativity/data/OLS.hpp