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

Ali A. Ismail

Physica A: Statistical Mechanics and its Applications, 2019, vol. 520, issue C, 138-150

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.

Keywords: Reliability; Statistical inference; Maximum likelihood; Bootstrap; MCMC (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:520:y:2019:i:c:p:138-150

DOI: 10.1016/j.physa.2019.01.004

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