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On partially observed competing risks model for Chen distribution under generalized progressive hybrid censoring

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  • Kundan Singh
  • Amulya Kumar Mahto
  • Yogesh Mani Tripathi

Abstract

In this paper, we discuss the inference for the competing risks model when the failure times follow Chen distribution. With assumption of two causes of failures, which are partially observed, are considered as independent. The existence and uniqueness of maximum likelihood estimates for model parameters are obtained under generalized progressive hybrid censoring. Also, we discussed the classical and Bayesian inferences of the model parameters under the assumption of restricted and nonrestricted parameters. Performance of classical point and interval estimators are compared with Bayesian point and interval estimators by conducting extensive simulation study. In addition to that, for illustration purpose, a real life example is discussed. Finally, some concluding remarks, regarding the presented model, are made.

Suggested Citation

  • Kundan Singh & Amulya Kumar Mahto & Yogesh Mani Tripathi, 2024. "On partially observed competing risks model for Chen distribution under generalized progressive hybrid censoring," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(1), pages 105-135, February.
    • Handle: RePEc:bla:stanee:v:78:y:2024:i:1:p:105-135
    DOI: 10.1111/stan.12308
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    References listed on IDEAS

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    1. Wang, Liang & Tripathi, Yogesh Mani & Lodhi, Chandrakant & Zuo, Xuanjia, 2022. "Inference for constant-stress Weibull competing risks model under generalized progressive hybrid censoring," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 70-83.
    2. Liang Wang & Ke Wu & Yogesh Mani Tripathi & Chandrakant Lodhi, 2022. "Reliability analysis of multicomponent stress–strength reliability from a bathtub-shaped distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(1), pages 122-142, January.
    3. Manoj Kumar Rastogi & Yogesh Mani Tripathi & Shuo-Jye Wu, 2012. "Estimating the parameters of a bathtub-shaped distribution under progressive type-II censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2389-2411, July.
    4. Sanku Dey & Liang Wang & Mazen Nassar, 2022. "Inference on Nadarajah–Haghighi distribution with constant stress partially accelerated life tests under progressive type-II censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(11), pages 2891-2912, August.
    5. Cramer, Erhard & Schmiedt, Anja Bettina, 2011. "Progressively Type-II censored competing risks data from Lomax distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1285-1303, March.
    6. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.
    7. Rui Hua & Wenhao Gui, 2022. "Inference for copula-based dependent competing risks model with step-stress accelerated life test under generalized progressive hybrid censoring," Computational Statistics, Springer, vol. 37(5), pages 2399-2436, November.
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