is.bma

classes

Bayesian Model Averaging for linear models with a wide choice of (customizable) priors. Built-in priors include coefficient priors (fixed, hyper-g and empirical priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches. Post-processing functions allow for inferring posterior inclusion and model probabilities, various moments, coefficient and predictive densities. Plotting functions available for posterior model size, MCMC convergence, predictive and coefficient densities, best models representation, BMA comparison. Also includes Bayesian normal-conjugate linear model with Zellner's g prior, and assorted methods.

Stefan Zeugner

Bayesian Model Averaging Library

is.bma function

<dl><dt>bmao</dt>
<dd>a 'bma' object: see 'value'</dd></dl>

Arguments

Tests for a 'bma' Object — is.bma

<dl>

<dt>bmao</dt>
<dd>a 'bma' object: see 'value'</dd>

</dl>

is.bma: Tests for a 'bma' Object

Description

Usage

Value

Arguments

See Also

Examples