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conting: an R package for Bayesian analysis of complete and incomplete contingency tables

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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.
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Original languageEnglish
Pages (from-to)1-27
JournalJournal of Statistical Software
Volume58
Issue number7
DOIs
StatePublished - Jun 2014

    Research areas

  • Contingency tables, Capture-recapture studies, Reversible jump, Log-linear models

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