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Multi-criteria-based optimal life-testing plans under hybrid censoring scheme

Author

Listed:
  • Ritwik Bhattacharya

    (Tecnológico de Monterrey
    Centro de Investigación en Matemáticas (CIMAT))

  • Baidya Nath Saha

    (Centro de Investigación en Matemáticas (CIMAT))

  • Graceila González Farías

    (Centro de Investigación en Matemáticas (CIMAT))

  • Narayanaswamy Balakrishnan

    (McMaster University)

Abstract

In designing an optimal life-testing experiment under censoring setup, the design parameters are usually chosen by optimizing a suitable criterion function. The criterion function is chosen by using either a variance-based or a cost-based model, and sometimes a combination of both these factors. However, it is an optimization problem with a single objective function. In this article, a multi-criteria-based optimization problem is considered in the context of hybrid censored life-testing experiment. Both the variance and the cost factors are optimized simultaneously. The exact distribution of the maximum likelihood estimate of the lifetime model parameter is used to construct the optimality criteria. All the proposed methods are illustrated through numerical examples. One dataset is finally analyzed for real-life applications.

Suggested Citation

  • Ritwik Bhattacharya & Baidya Nath Saha & Graceila González Farías & Narayanaswamy Balakrishnan, 2020. "Multi-criteria-based optimal life-testing plans under hybrid censoring scheme," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 430-453, June.
    • Handle: RePEc:spr:testjl:v:29:y:2020:i:2:d:10.1007_s11749-019-00660-8
    DOI: 10.1007/s11749-019-00660-8
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    References listed on IDEAS

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    1. Ritwik Bhattacharya & Biswabrata Pradhan, 2017. "Computation of optimum Type-II progressively hybrid censoring schemes using variable neighborhood search algorithm," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 802-821, December.
    2. R. Bhattacharya & B. Pradhan & A. Dewanji, 2014. "Optimum life testing plans in presence of hybrid censoring: A cost function approach," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 30(5), pages 519-528, September.
    3. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.
    4. Bhattacharya, Ritwik & Pradhan, Biswabrata & Dewanji, Anup, 2015. "Computation of optimum reliability acceptance sampling plans in presence of hybrid censoring," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 91-100.
    5. Balakrishnan, N. & Burkschat, Marco & Cramer, Erhard & Hofmann, Glenn, 2008. "Fisher information based progressive censoring plans," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 366-380, December.
    6. A. Childs & B. Chandrasekar & N. Balakrishnan & D. Kundu, 2003. "Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(2), pages 319-330, June.
    7. Nader Ebrahimi, 1988. "Determining the sample size for a hybrid life test based on the cost function," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(1), pages 63-72, February.
    8. Yao Zhang & William Q. Meeker, 2005. "Bayesian life test planning for the Weibull distribution with given shape parameter," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 61(3), pages 237-249, June.
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    Cited by:

    1. Mao Song & Liu Bin & Shi Yimin, 2021. "Statistical Inference for a Simple Step Stress Model with Competing Risks Based on Generalized Type-I Hybrid Censoring," Journal of Systems Science and Information, De Gruyter, vol. 9(5), pages 533-548, October.
    2. Narayanaswamy Balakrishnan & Ritwik Bhattacharya, 2022. "Revisiting Best Linear Unbiased Estimation of Location-Scale Parameters Based on Optimally Selected Order Statistics Using Compound Design," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1891-1915, September.

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