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BAS (version 1.4.7)

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 dertermine the penalty.

See Also

g.prior

Other beta priors: CCH, EB.local, Jeffreys, TG, beta.prime, g.prior, hyper.g.n, hyper.g, intrinsic, robust, tCCH, testBF.prior

Examples

Run this code
# NOT RUN {
IC.prior(2)
          aic.prior()
          bic.prior(100)
          
# }

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