Using the Reversible Jump MCMC Procedure for Identifying and Estimating Univariate TAR Models

DOI10.1080/03610918.2012.655827zbMath1433.62266OpenAlexW2008740744MaRDI QIDQ4921600

Wen Li, Fabio H. Nieto, Han-Wen Zhang

Publication date: 13 May 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.655827

zbMATH Keywords

nonlinear time seriesregime-switching modelsBayesian model choiceRJMCMCthreshold autoregressive (TAR) models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (2)

Bayesian inference of smooth transition autoregressive (STAR)\((k)\)-GARCH\((l, m)\) models ⋮ Bayesian analysis of multivariate threshold autoregressive models with missing data

Cites Work

• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Forecasting with univariate TAR models
• Monte Carlo methods in Bayesian computation
• Bayesian selection of threshold autoregressive models
• Reversible Jump Markov Chain Monte Carlo Strategies for Bayesian Model Selection in Autoregressive Processes
• Modeling Bivariate Threshold Autoregressive Processes in the Presence of Missing Data
• Unnamed Item

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