Bayesian Analysis

Bayesian Model Selection for Beta Autoregressive Processes

Roberto Casarin, Luciana Dalla Valle, and Fabrizio Leisen

Full-text: Open access

Abstract

We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of parameter and model priors with possible parameter restrictions and suggest a Reversible Jump Markov-Chain Monte Carlo (RJMCMC) procedure based on a Metropolis-Hastings within Gibbs algorithm.

Article information

Source
Bayesian Anal., Volume 7, Number 2 (2012), 385-410.

Dates
First available in Project Euclid: 16 June 2012

Permanent link to this document
https://projecteuclid.org/euclid.ba/1339878893

Digital Object Identifier
doi:10.1214/12-BA713

Mathematical Reviews number (MathSciNet)
MR2934956

Zentralblatt MATH identifier
1330.62113

Keywords
Bayesian Inference Beta Autoregressive Processes Reversible Jump MCMC

Citation

Casarin, Roberto; Dalla Valle, Luciana; Leisen, Fabrizio. Bayesian Model Selection for Beta Autoregressive Processes. Bayesian Anal. 7 (2012), no. 2, 385--410. doi:10.1214/12-BA713. https://projecteuclid.org/euclid.ba/1339878893


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