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Assessing the Lifetime Performance Index with Digital Inferences of Power Hazard Function Distribution Using Progressive Type-II Censoring Scheme.

Rashad M El-SagheerTaghreed M JawaNeveen Sayed-Ahmed
Published in: Computational intelligence and neuroscience (2022)
This paper deals with estimating the lifetime performance index. The maximum likelihood (ML) and Bayesian estimators for lifetime performance index C L X where L X is the lower specification limit are derived based on progressive type-II censored (Prog-Type-II-C) sample from two-parameter power hazard function distribution (PHFD). Knowing the lower specification limit, the MLE of C L X is applied to construct a new hypothesis testing procedure. Bayesian estimator of C L X is also utilized to develop a credible interval. Also, the relationship between the C L X and the conforming rate of products is investigated. Moreover, the Bayesian test to evaluate the lifetime performance of units is proposed. A simulation study and illustrative example based on a real dataset are discussed to evaluate the performance of the two tests.
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