Bayesian analysis of two-regime threshold autoregressive moving average model with exogenous inputs

Qiang Xia, Jinshan Liu, Jiazhu Pan, Rubing Liang

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

We consider Bayesian analysis of threshold autoregressive moving average model with exogenous inputs (TARMAX). In order to obtain the desired marginal posterior distributions of all parameters including the threshold value of the two-regime TARMAX model, we use two different Markov chain Monte Carlo (MCMC) methods to apply Gibbs sampler with Metropolis-Hastings algorithm. The first one is used to obtain iterative least squares estimates of the parameters. The second one includes two MCMC stages for estimate the desired marginal posterior distributions and the parameters. Simulation experiments and a real data example show support to our approaches.

Original languageEnglish
Pages (from-to)1089-1104
Number of pages16
JournalCommunications in Statistics - Simulation and Computation
Volume41
Issue number6
Early online date10 Feb 2012
DOIs
Publication statusPublished - 2012

Keywords

  • Bayesian analysis
  • Gibbs sampler
  • Metropolis-Hastings algorithm
  • TARMAX model

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