2 #include "creativity/data/Equation.hpp"    45         int df()
 const { 
return n() - 
k(); }
    64         const Eigen::VectorXd& 
beta() 
const;
    77         const Eigen::VectorXd& 
se() 
const;
    83         const Eigen::VectorXd& 
tRatios() 
const;
    89         const Eigen::VectorXd& 
pValues() 
const;
    95         const double& 
s2() 
const;
   101         const Eigen::VectorXd& 
residuals() 
const;
   107         const double& 
ssr() 
const;
   117         const double& 
Rsq() 
const;
   139         const Eigen::VectorXd& 
y() 
const;
   146         const Eigen::MatrixXd& 
X() 
const;
   152         friend std::ostream& 
operator<<(std::ostream &os, 
const OLS &ols);
   192         void requireGathered()
 const { 
if (!gathered_) 
throw std::logic_error(
"Cannot access model data before calling gather()"); }
   195         void requireSolved()
 const { 
if (!solved_) 
throw std::logic_error(
"Cannot obtain model estimates before calling solve()"); }
 Class for running a basic OLS regression. 
Definition: OLS.hpp:17
 
Equation model_
The model, given during construction. 
Definition: OLS.hpp:155
 
const Equation & model() const
Accesses the model used for this OLS object. 
Definition: OLS.hpp:32
 
double p
The p-value of the test. 
Definition: OLS.hpp:124
 
Eigen::VectorXd y_
The y vector generated from the model. 
Definition: OLS.hpp:161
 
double f
The F value. 
Definition: OLS.hpp:121
 
The return value of fStat() 
Definition: OLS.hpp:120
 
const double & ssr() const
Returns the sum-of-squared residuals. 
 
Eigen::VectorXd p_values_
Cached p-values. 
Definition: OLS.hpp:182
 
Eigen::MatrixXd X_
The X matrix generated from the model. 
Definition: OLS.hpp:164
 
friend 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 fo...
 
Primary namespace for all Creativity library code. 
Definition: config.hpp:4
 
bool gathered_
Whether gather() has been called, to populate y_ and X_. 
Definition: OLS.hpp:158
 
Eigen::VectorXd beta_
The beta vector. 
Definition: OLS.hpp:170
 
double ssr_
SSR. 
Definition: OLS.hpp:187
 
Eigen::VectorXd se_
Cached standard errors. 
Definition: OLS.hpp:176
 
const Eigen::VectorXd & se() const
Returns the standard errors (the square roots of the diagonal of covariance()) of the beta() values...
 
Eigen::VectorXd residuals_
Residuals. 
Definition: OLS.hpp:185
 
int df() const
Returns the degrees of freedom of the model; this is simply n() - k(). 
Definition: OLS.hpp:45
 
Class to store a equation. 
Definition: Equation.hpp:33
 
const Eigen::VectorXd & y() const
Returns the y data used to solve the model. 
 
double R2_
R^2 value. 
Definition: OLS.hpp:189
 
bool solved_
Whether solve() has been called, to populate the below. 
Definition: OLS.hpp:167
 
void gather()
Calculates and stores the final numerical values from the model. 
 
std::shared_ptr< const Variable > depVar() const
Accesses the dependent variable. 
 
const Eigen::VectorXd & tRatios() const
Returns the t-ratios for =0 tests, i.e. 
 
const Eigen::MatrixXd & covariance() const
Returns the covariance estimate of the beta estimators. 
 
const double & Rsq() const
Returns the  value for the regression. 
 
const double & s2() const
Returns , the square of the regression standard error. 
 
OLS()=delete
No default constructor. 
 
Eigen::MatrixXd var_beta_
The estimated covariance of the beta estimators. 
Definition: OLS.hpp:173
 
void requireSolved() const
Throws a std::logic_error if the model hasn't been solved. 
Definition: OLS.hpp:195
 
unsigned df_denominator
Denominator d.f. 
Definition: OLS.hpp:123
 
ftest fTest() const
Calculates and returns the F-test of all non-constant coefficients in the model being equal to 0...
 
void requireGathered() const
Throws a std::logic_error if the model hasn't been gathered. 
Definition: OLS.hpp:192
 
void solve()
Attempts to solve the model, if not already done. 
 
Eigen::VectorXd t_ratios_
Cached t ratios. 
Definition: OLS.hpp:179
 
double s2_
sigma^2 estimate 
Definition: OLS.hpp:188
 
unsigned int n() const
Returns the number of observations for this OLS object. 
Definition: OLS.hpp:36
 
const Eigen::MatrixXd & X() const
Returns the X data used to solve the model. 
 
unsigned int numVars() const
Returns the number of independent variables. 
 
const Eigen::VectorXd & residuals() const
Returns the residuals. 
 
unsigned int k() const
Returns the number of variables for this OLS object. 
Definition: OLS.hpp:40
 
unsigned df_numerator
Numerator d.f. 
Definition: OLS.hpp:122
 
const Eigen::VectorXd & beta() const
Returns the vector of coefficients (i.e. 
 
const Eigen::VectorXd & pValues() const
Returns the p-values of the t-ratios returned by tRatios()