bayesloglin {bayesloglin}R Documentation

Bayesian analysis of contingency table data

Description

Functions for Bayesian model selection and inference for log-linear models.

Details

Package: bayesloglin
Type: Package
Version: 1.0
Date: 2016-12-23
License: GPL-2

The function MC3 searches for log-linear models with the highest posterior probability. The function gibbsSampler is a blocked Gibbs sampler for sampling fronm the posterior distribution of the log-linear parameters. The functions findPostMean and findPostCov compute the posterior mean and covariance matrix for decomposable models which, for these models, is available in closed form.

Author(s)

Author: Matthew Friedlander Maintainer: Matthew Friedlander <friedla@yorku.ca>

References

see vignette

Examples

data(czech)
s1 <- MC3 (init = NULL, alpha = 1, iterations = 5, 
           replicates = 1, data = czech, mode = "Decomposable")
s2 <- MC3 (init = NULL, alpha = 1, iterations = 5,   
            replicates = 1, data = czech, mode = "Graphical")
s3 <- MC3 (init = NULL, alpha = 1, iterations = 5,   
            replicates = 1, data = czech, mode = "Hierarchical")

[Package bayesloglin version 1.0.1 Index]