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Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals

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  • Manoj Chacko

    (University of Kerala)

  • Rakhi Mohan

    (University of Kerala)

Abstract

In medical studies or reliability analysis, the failure of individuals or items may be due to more than one cause or factor. These risk factors in some sense compete for the failure of the experimental units. Analysis of data in this circumstances is called competing risks analysis. In this paper, we consider the analysis of competing risk data under progressive type-II censoring by assuming the number of units removed at each stage is random and follows a binomial distribution. Bayes estimators are obtained by assuming the population under consider follows a Weibull distribution. A simulation study is carried out to study the performance of the different estimators derived in this paper. A real data set is also used for illustration.

Suggested Citation

  • Manoj Chacko & Rakhi Mohan, 2019. "Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals," Computational Statistics, Springer, vol. 34(1), pages 233-252, March.
    • Handle: RePEc:spr:compst:v:34:y:2019:i:1:d:10.1007_s00180-018-0847-2
    DOI: 10.1007/s00180-018-0847-2
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    References listed on IDEAS

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    1. 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.
    2. Siu Keung Tse & Chunyan Yang & Hak-Keung Yuen, 2000. "Statistical analysis of Weibull distributed lifetime data under Type II progressive censoring with binomial removals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(8), pages 1033-1043.
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    4. Rita Aggarwala & N. Balakrishnan, 1996. "Recurrence relations for single and product moments of progressive Type-II right censored order statistics from exponential and truncated exponential distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(4), pages 757-771, December.
    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. Pareek, Bhuvanesh & Kundu, Debasis & Kumar, Sumit, 2009. "On progressively censored competing risks data for Weibull distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4083-4094, October.
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    Cited by:

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    3. Hanan Haj Ahmad & Mohamed Aboshady & Mahmoud Mansour, 2024. "The Role of Risk Factors in System Performance: A Comprehensive Study with Adaptive Progressive Type-II Censoring," Mathematics, MDPI, vol. 12(11), pages 1-21, June.
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    5. Jiaxin Nie & Wenhao Gui, 2019. "Parameter Estimation of Lindley Distribution Based on Progressive Type-II Censored Competing Risks Data with Binomial Removals," Mathematics, MDPI, vol. 7(7), pages 1-15, July.

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