Conting: An R package for bayesian analysis of complete and incomplete contingency tables

The aim of this paper is to demonstrate the r package conting for the bayesian analysis of complete and incomplete contingency tables using hierarchical log-linear models. this package allows a user to identify interactions between categorical factors (via complete contingency tables) and to estimate closed population sizes using capture-recapture studies (via incomplete contingency tables). the models are fitted using markov chain monte carlo methods. in particular,implementations of the metropolis-hastings and reversible jump algorithms appropriate for log-linear models are employed. the conting package is demonstrated on four real examples. © 2014,american statistical association. all rights reserved.