ctable

Computes a Bayes factor against independence for a two-way contingency table assuming
uniform prior distributions

models

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

ctable function

<dl> <dt>y</dt>
<dd>matrix of counts</dd> <dt>a</dt>
<dd>matrix of prior hyperparameters</dd></dl>

Arguments

Author

Bayes factor against independence using uniform priors — ctable

<dl>

 <dt>y</dt>
<dd>matrix of counts</dd>

 <dt>a</dt>
<dd>matrix of prior hyperparameters</dd>

</dl>

ctable: Bayes factor against independence using uniform priors

Description

Usage

Value

Arguments

Author

Examples