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R package for Bayes factors

Richard Morey writes:

You and your blog readers may be interested to know that a we’ve released a major new version of the BayesFactor package to CRAN. The package computes Bayes factors for linear mixed models and regression models. Of course, I’m aware you don’t like point-null model comparisons, but the package does more than that; it also allows sampling from posterior distributions of the compared models, in much the same way that your arm package does with lmer objects. The sampling (both for the Bayes factors and posteriors) is quite fast, since the back end is written in C.

Some basic examples using the package can be found here, and the CRAN page is here.

Indeed I don’t like point-null model comparisons . . . but maybe this will be useful to some of you!


  1. C Ryan King says:

    It’s not clear from the writeup what kind of MCMC is being done for the posterior sampling. RW on the likelihood marginal on the random effects? Gibbs?

  2. Richard Morey says:

    The posterior sampling is just Gibbs, using the models defined in the Liang et al (2008) and Rouder et al (2012).