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An efficient algorithm for estimating a change-point

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  • Cheng, Tsung-Lin

Abstract

In this paper, we propose an efficient algorithm to remedy the drawbacks in the implementations of some renowned CUSUM-type estimations. The new approach not only reduces the computational time dramatically but also gives a much simpler proof of the consistency of the estimator of a change-point. The simulation study is conducted to illustrate the computational power of the proposed algorithm.

Suggested Citation

  • Cheng, Tsung-Lin, 2009. "An efficient algorithm for estimating a change-point," Statistics & Probability Letters, Elsevier, vol. 79(5), pages 559-565, March.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:5:p:559-565
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    References listed on IDEAS

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    4. Bhattacharya, P.K., 1987. "Maximum likelihood estimation of a change-point in the distribution of independent random variables: General multiparameter case," Journal of Multivariate Analysis, Elsevier, vol. 23(2), pages 183-208, December.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    6. Gombay Edit & Horváth Lajos & Husková Marie, 1996. "Estimators And Tests For Change In Variances," Statistics & Risk Modeling, De Gruyter, vol. 14(2), pages 145-160, February.
    7. Henghsiu Tsai & K. S. Chan, 2005. "Maximum likelihood estimation of linear continuous time long memory processes with discrete time data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 703-716, November.
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    Cited by:

    1. Qin, Ruibing & Tian, Zheng & Jin, Hao & Zhang, Xiaowei, 2010. "Strong convergence rate of robust estimator of change point," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2026-2032.
    2. Cheng, Tsung-Lin & Wang, Jheng-Ting, 2020. "A computationally efficient approach on detecting star-shaped change boundaries in random fields with heavy-tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 169(C), pages 16-25.

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