The LaplacesDemon package in R enables Bayesian inference with any Bayesian model, provided the user specifies the likelihood. This vignette is a compendium of examples of how to specify different model forms.

We propose the use of the generalized fractional Bayes factor for testing fit in multinomial models. This is a non-asymptotic method that can be used to quantify the evidence for or against a sub-model. We give expressions for the generalized fractional Bayes factor and we study its properties. In particular, we show that the generalized fractional Bayes factor has better properties than the fractional Bayes factor. Keywords: generalized fractional Bayes factor, Dirichlet process, Beta-Stacy process. 1. Introduction. In this paper we propose a Bayesian method for testing fit in multinomial models. Specifically, we will use the Bayes factor for evaluating the evidence for or against a null sub-model of the multinomial. The advantages of using a Bayesian approach for this problem are that it does not rely