IC.prior: Information Criterion Families of Prior Distribution for Coefficients in BMA
Models
Description
Creates an object representing the prior distribution on coefficients for
BAS.
Usage
IC.prior(penalty)
Arguments
penalty
a scalar used in the penalized loglikelihood of the form
penalty*dimension
Value
returns an object of class "prior", with the family and
hyerparameters.
Details
The log marginal likelihood is approximated as -2*(deviance +
penalty*dimension). Allows alternatives to AIC (penalty = 2) and BIC
(penalty = log(n)). For BIC, the argument may be missing, in which case the
sample size is determined from the call to `bas.glm` and used to determine
the penalty.