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2015
ACM

de Finetti Priors using Markov chain Monte Carlo computations

3 years 5 months ago
de Finetti Priors using Markov chain Monte Carlo computations
Recent advances in Monte Carlo methods allow us to revisit work by de Finetti who suggested the use of approximate exchangeability in the analyses of contingency tables. This paper gives examples of computational implementations using Metropolis Hastings, Langevin and Hamiltonian Monte Carlo to compute posterior distributions for test statistics relevant for testing independence, reversible or three way models for discrete exponential families using polynomial priors and Gr¨obner bases. AMS subject classification: 62C10, 62C25. Key words and phrases: Priors, MCMC, Contingency Tables, Bayesian Inference, Independence.
Sergio Bacallado, Persi Diaconis, Susan Holmes
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where SAC
Authors Sergio Bacallado, Persi Diaconis, Susan Holmes
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