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Statistical analysis of Type-I progressively hybrid censored data under constant-stress life testing model

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  • Ismail, Ali A.

Abstract

In this article we consider the reliability analysis problem of constant-stress life test model based on progressively Type-I hybrid censored data from Weibull distribution. Three different methods; maximum likelihood (ML), percentile bootstrap (PB) and Markov Chain Monte Carlo (MCMC) are applied to construct statistical inference on the model parameters. To evaluate the performance of these methods toward the obtained estimates, the associated mean squared errors (MSEs) are calculated. Besides, the confidence limits of the model parameters and their coverage probabilities are calculated. Finally, an extensive simulation study has been performed to illustrate the theoretical results based on this advanced censoring scheme and assess the performance of the proposed methods.

Suggested Citation

  • Ismail, Ali A., 2019. "Statistical analysis of Type-I progressively hybrid censored data under constant-stress life testing model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 138-150.
    • Handle: RePEc:eee:phsmap:v:520:y:2019:i:c:p:138-150
    DOI: 10.1016/j.physa.2019.01.004
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    1. Ling, Li & Xu, Wei & Li, Minghai, 2009. "Parametric inference for progressive Type-I hybrid censored data on a simple step-stress accelerated life test model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(10), pages 3110-3121.
    2. Morris H. Degroot & Prem K. Goel, 1979. "Bayesian estimation and optimal designs in partially accelerated life testing," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 26(2), pages 223-235, June.
    3. Lin, Chien-Tai & Chou, Cheng-Chieh & Huang, Yen-Lung, 2012. "Inference for the Weibull distribution with progressive hybrid censoring," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 451-467.
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