aic: Information Criterion for model selection
In efriedland/friedland: Making Functions Do Your Econometrics For You

Description Usage Arguments Details Examples

Used for model selection.

1 2	aic(model) bic(model)

model

A model.

aic() is to be used when comparing lags. bic() is to be used when comparing lags & leads.

## The functions are currently defined as
aic <- function(model){
  n <- df.residual(model) + length(variable.names(model))
  log(sum(resid(model) ^ 2) / n) + (length(variable.names(model)) / n) * 2
} 
bic <- function(model){
    n <- df.residual(model) + length(variable.names(model))
    log(sum(resid(model) ^ 2) / n) + length(variable.names(model)) * log(n) / n
  }