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Permutation tests in change point analysis

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  • Antoch, Jaromír
  • Husková, Marie

Abstract

The critical values for various tests for changes in location model are obtained through the use of permutation tests principle. Theoretical results show that in the limit these new "permutation tests" behave in the same way as the "classical tests" stemming from both maximum likelihood and Bayes principles. However, the results of the simulation study show that the permutation tests behave considerably better than the corresponding classical tests if measured by the critical values attained.

Suggested Citation

  • Antoch, Jaromír & Husková, Marie, 2001. "Permutation tests in change point analysis," Statistics & Probability Letters, Elsevier, vol. 53(1), pages 37-46, May.
    • Handle: RePEc:eee:stapro:v:53:y:2001:i:1:p:37-46
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    References listed on IDEAS

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    1. Husková, M., 1997. "Limit theorems for rank statistics," Statistics & Probability Letters, Elsevier, vol. 32(1), pages 45-55, February.
    2. Gombay, Edit & Horváth, Lajos, 1996. "On the Rate of Approximations for Maximum Likelihood Tests in Change-Point Models," Journal of Multivariate Analysis, Elsevier, vol. 56(1), pages 120-152, January.
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    Cited by:

    1. Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
    2. Marie Hušková & Claudia Kirch, 2008. "Bootstrapping confidence intervals for the change‐point of time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 947-972, November.
    3. Kirch Claudia, 2007. "Resampling in the frequency domain of time series to determine critical values for change-point tests," Statistics & Risk Modeling, De Gruyter, vol. 25(3), pages 237-261, July.
    4. Federico A. Bugni & Jia Li & Qiyuan Li, 2023. "Permutation‐based tests for discontinuities in event studies," Quantitative Economics, Econometric Society, vol. 14(1), pages 37-70, January.
    5. Barbora Peštová & Michal Pešta, 2018. "Abrupt change in mean using block bootstrap and avoiding variance estimation," Computational Statistics, Springer, vol. 33(1), pages 413-441, March.
    6. Marie Hušková & Claudia Kirch, 2012. "Bootstrapping sequential change-point tests for linear regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(5), pages 673-708, July.
    7. Holmes, Mark & Kojadinovic, Ivan & Quessy, Jean-François, 2013. "Nonparametric tests for change-point detection à la Gombay and Horváth," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 16-32.
    8. Cho, Haeran & Kirch, Claudia, 2022. "Bootstrap confidence intervals for multiple change points based on moving sum procedures," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    9. Mohamed Salah Eddine Arrouch & Echarif Elharfaoui & Joseph Ngatchou-Wandji, 2023. "Change-Point Detection in the Volatility of Conditional Heteroscedastic Autoregressive Nonlinear Models," Mathematics, MDPI, vol. 11(18), pages 1-31, September.
    10. Marie Hušková & Simos Meintanis, 2006. "Change Point Analysis based on Empirical Characteristic Functions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 63(2), pages 145-168, April.
    11. Tabacu, Lucia & Ledbetter, Mark, 2019. "Change-point analysis using logarithmic quantile estimation," Statistics & Probability Letters, Elsevier, vol. 150(C), pages 94-100.
    12. Jean-François Quessy, 2019. "Consistent nonparametric tests for detecting gradual changes in the marginals and the copula of multivariate time series," Statistical Papers, Springer, vol. 60(3), pages 717-746, June.

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