Synthetic detection of change point and outliers in bilinear time series models

Ping Chen, Jing Yang and Linyuan Li

International Journal of Systems Science, 2015, vol. 46, issue 2, 284-293

Abstract: This paper proposes a procedure of synthetic detection for the location of a change point and outliers in bilinear time series models with a change after an unknown time point. Based on Bayesian framework, we first derive the conditional posterior distribution of the change point and from that distribution estimate the position of the change point. Then we use these results to detect the outliers in the time series before and after that change point via Gibbs sampler algorithm. Our simulation studies show that the proposed procedure is effective.

Date: 2015
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DOI: 10.1080/00207721.2013.777983

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