lm

Functionality for basic OLS regression. More will be added.

struct LMFit

Holds the output of a regression.

• Vector beta(): Vector of coefficients
• List coefficients(): Coefficients plus standard errors and other information, as provided by summary
• Vector residuals()
• Vector fittedValues()
• int dfResidual()
• List model()
• double sigma()
• double rsq()
• double adjrsq()
• double fstat()
  
• List unscaledCov()
• void print(string msg=""): Print the output provided by lm (not summary), with an optional message
• double pred(double x): Makes a prediction with new data x, assuming this is a simple linear regression (one regressor)
• double pred(Vector x): Makes a prediction with new data x, for any number of regressors. Automatically handles the intercept, so you should not include a 1 or any other number in x to account for the intercept.

Estimation

• LMFit lm(T1, T2)(T1 y, T2 x)
• LMFit lm(T1, T2)(T1 y, T2 x, LMConfig conf)
• LMFit lm(DataFrame df, LMConfig conf)

struct LMConfig

Configuration for a regression.

• string lhs
• string[] rhs
• bool intercept = true
• Subset subset

Index    Repo