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Convergence of the CUSUM estimation for a mean shift in linear processes with random coefficients

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Listed:
  • Yi Wu

    (Chizhou University)

  • Wei Wang

    (Chizhou University)

  • Xuejun Wang

    (Anhui University)

Abstract

Let $$\{X_{i},1\le i\le n\}$$ { X i , 1 ≤ i ≤ n } be a sequence of linear process based on dependent random variables with random coefficients, which has a mean shift at an unknown location. The cumulative sum (CUSUM, for short) estimator of the change point is studied. The strong convergence, $$L_{r}$$ L r convergence, complete convergence and the rate of strong convergence are established for the CUSUM estimator under some mild conditions. These results improve and extend the corresponding ones in the literature. Simulation studies and two real data examples are also provided to support the theoretical results.

Suggested Citation

  • Yi Wu & Wei Wang & Xuejun Wang, 2024. "Convergence of the CUSUM estimation for a mean shift in linear processes with random coefficients," Computational Statistics, Springer, vol. 39(7), pages 3753-3778, December.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:7:d:10.1007_s00180-024-01465-6
    DOI: 10.1007/s00180-024-01465-6
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    References listed on IDEAS

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