[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/CKSS.2003.10.3.981

Bayesian Inference for Switching Mean Models with ARMA Errors

Son, Young Sook (Department of Statistics, Chonnam National University)
Kim, Seong W. (Division of Applied Mathematics, Hanyang University)
Cho, Sinsup (Department of Statistics, Seoul National University)

Publication Information

Communications for Statistical Applications and Methods / v.10, no.3, 2003 , pp. 981-996 More about this Journal

Abstract

Bayesian inference is considered for switching mean models with the ARMA errors. We use noninformative improper priors or uniform priors. The fractional Bayes factor of O'Hagan (1995) is used as the Bayesian tool for detecting the existence of a single change or multiple changes and the usual Bayes factor is used for identifying the orders of the ARMA error. Once the model is fully identified, the Gibbs sampler with the Metropolis-Hastings subchains is constructed to estimate parameters. Finally, we perform a simulation study to support theoretical results.

Keywords

switching mean model; multiple change points; ARMA error; noninformative improper prior; fractional Bayes factor; Gibbs sampler; Metropolis-Hastings algorithm;

Citations & Related Records

Times Cited By KSCI : 1 (Citation Analysis)

Reference
Cited By KSCI

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