R: Information Criterion Families of Prior Distribution for...

IC.prior {BAS} | R Documentation

## 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

### 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.

### Value

returns an object of class "prior", with the family and hyerparameters.

### Author(s)

Merlise Clyde

### 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

    IC.prior(2)
    aic.prior()
    bic.prior(100)

[Package BAS version 1.5.5 Index]