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BAS (version 1.2.2)

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

hyerparameters.

Details

The log marginal likelihood is approximated as -2*(deviance + penalty*dimension). Allows alternatives to AIC (penalty = 2) and BIC (penalty = log(n))

See Also

g.prior

Examples

Run this code
          aic.prior()
          bic.prior(100)

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