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Testing for variance changes in autoregressive models with unknown order

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  • Baisuo Jin
  • Mong-Na Lo Huang
  • Baiqi Miao

Abstract

The problem of change point in autoregressive process is studied in this article. We propose a Bayesian information criterion-iterated cumulative sums of squares algorithm to detect the variance changes in an autoregressive series with unknown order. Simulation results and two examples are presented, where it is shown to have good performances when the sample size is relatively small.

Suggested Citation

  • Baisuo Jin & Mong-Na Lo Huang & Baiqi Miao, 2011. "Testing for variance changes in autoregressive models with unknown order," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 927-936, January.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:5:p:927-936
    DOI: 10.1080/02664761003692399
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    References listed on IDEAS

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    1. Bai, J., 1994. "Stochastic Equicontinuity and Weak Convergence of Unbounded Sequential Empirical Proceses," Working papers 94-07, Massachusetts Institute of Technology (MIT), Department of Economics.
    2. Sangyeol Lee & Siyun Park, 2001. "The Cusum of Squares Test for Scale Changes in Infinite Order Moving Average Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 625-644, December.
    3. Gombay, Edit, 2008. "Change detection in autoregressive time series," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 451-464, March.
    4. Sangyeol Lee & Jeongcheol Ha & Okyoung Na & Seongryong Na, 2003. "The Cusum Test for Parameter Change in Time Series Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(4), pages 781-796, December.
    5. B. Abraham & W. Wei, 1984. "Inferences about the parameters of a time series model with changing variance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 31(1), pages 183-194, December.
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