BAYESIAN ANALYSIS OF AUTOREGRESSIVE TIME SERIES VIA THE GIBBS SAMPLER

Robert McCulloch, Ruey S. Tsay

Research output: Contribution to journalArticlepeer-review

96 Scopus citations

Abstract

Abstract. Applications of the Gibbs Sampler in time series analysis are considered. We show that the sampler applies nicely to various problems in analyzing autoregressive processes and, in many cases, it enjoys certain advantages over the traditional methods. The problems considered include random level‐shift models, outliers and missing values. Real examples are used to illustrate the analysis.

Original languageEnglish (US)
Pages (from-to)235-250
Number of pages16
JournalJournal of Time Series Analysis
Volume15
Issue number2
DOIs
StatePublished - 1994
Externally publishedYes

Keywords

  • Missing value
  • outlier
  • posterior distribution
  • random level‐shift model

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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