Bayesian Information Criterion for Compound Poisson-Normal Models

Computes the Bayesian Information Criterion (BIC) for a fitted Compound Poisson-Normal (CPN) regression model.

Usage

BIC.cpn(object, ...)

Arguments

object

An object of class "cpn", typically the result of a call to cpn.

...

Additional arguments (currently unused).

Value

A numeric value representing the BIC of the fitted model.

Details

The BIC is computed as: $$-2 \cdot \log L + k \cdot \log(n)$$ where \(L\) is the likelihood of the fitted model, \(k\) is the number of estimated parameters (including regression coefficients, \(\mu\), and \(\sigma\)), and \(n\) is the number of observations.

See also

cpn, AIC, BIC