conting : an R package for Bayesian analysis of complete and incomplete contingency tables
Abstract
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.
Citation
Overstall , A & King , R 2014 , ' conting : an R package for Bayesian analysis of complete and incomplete contingency tables ' , Journal of Statistical Software , vol. 58 , no. 7 , pp. 1-27 . https://doi.org/10.18637/jss.v058.i07
Publication
Journal of Statistical Software
Status
Peer reviewed
Type
Journal article
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