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- Title
Adaptive Type-II Hybrid Progressive Censoring Samples for Statistical Inference of Comparative Inverse Weibull Distributions.
- Authors
Al-Essa, Laila A.; Soliman, Ahmed A.; Abd-Elmougod, Gamal A.; Alshanbari, Huda M.
- Abstract
Recently, there has been a lot of interest in comparative life testing for items under jointly censored schemes for products from multiple production lines. The inverse Weibull distribution (IWD) is commonly used in life testing and reliability theory. In this paper, we address the problem of statistical inference from comparative inverse Weibull distributions under joint samples. An adaptive type-II hybrid progressive censoring scheme (HPCS) is used to save the balance between the ideal test time and the number of observed failures. Under the adaptive type-II HPCS, unknown parameters of the inverse Weibull populations are estimated using both maximum likelihood and Bayesian approaches. Asymptotic confidence intervals are established using the observed Fisher information matrix and bootstrap confidence intervals. We suggest using Markov chain Monte Carlo (MCMC) techniques to compute credible intervals under independent gamma priors. Using Monte Carlo simulations, all theoretical conclusions are tested and contrasted. For illustration purposes, an actual sample from comparative populations is analysed.
- Subjects
WEIBULL distribution; STATISTICAL sampling; MONTE Carlo method; MARKOV chain Monte Carlo; BAYES' estimation; FISHER information; INFERENTIAL statistics; ENGINEERING reliability theory; STATISTICAL bootstrapping
- Publication
Axioms (2075-1680), 2023, Vol 12, Issue 10, p973
- ISSN
2075-1680
- Publication type
Article
- DOI
10.3390/axioms12100973