Bayesian analysis of autoregressive moving average processes with unknown orders

DOI10.1016/j.csda.2005.12.005zbMath1157.62365OpenAlexW1994982764MaRDI QIDQ1010539

Anne Philippe

Publication date: 6 April 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2005.12.005

zbMATH Keywords

model selectionpoint processinvertibilitystationaritylatent variablesbirth-death processMCMC algorithm

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (5)

Bayesian temporal density estimation with autoregressive species sampling models ⋮ Bayesian model selection for unit root testing with multiple structural breaks ⋮ Bayesian modeling and forecasting of vector autoregressive moving average processes ⋮ Prediction in several conventional contexts ⋮ Bayesian subset selection for threshold autoregressive moving-average models

Uses Software

• spatial

Cites Work

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• Reversible Jump Markov Chain Monte Carlo Strategies for Bayesian Model Selection in Autoregressive Processes
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• Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.

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