A Bayesian analysis of a change in the parameters of autoregressive time series. Issue 9 (21st October 2017)

• Record Type: Journal Article
• Authors: Slama, Abdeldjalil; Saggou, Hafida
• Is Part Of: Communications in statistics. Volume 46:Issue 9(2017)
• Page Start: 7008
• Page End: 7021
• Publication Date: 2017-10-21
• Subjects: Autoregressive model -- Bayesian analysis -- Change point -- Gibbs sampler -- HPD credible set -- p-Values; 62M10 -- 62F15 -- 62F03; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2016.1222423
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: In this article, we consider a Bayesian analysis of a possible change in the parameters of autoregressive time series of known order p, AR( p ). An unconditional Bayesian test based on highest posterior density (HPD) credible sets is determined. The test is useful to detect a change in any one of the parameters separately. Using the Gibbs sampler algorithm, we approximate the posterior densities of the change point and other parameters to calculate the p -values that define our test.