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

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This paper deals with estimating the lifetime performance index. The maximum likelihood (ML) and Bayesian estimators for lifetime performance index CLX where LX is the lower specification limit are derived… Click to show full abstract

This paper deals with estimating the lifetime performance index. The maximum likelihood (ML) and Bayesian estimators for lifetime performance index CLX where LX 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 CLX is applied to construct a new hypothesis testing procedure. Bayesian estimator of CLX is also utilized to develop a credible interval. Also, the relationship between the CLX 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.

Keywords: power hazard; progressive type; performance index; lifetime performance; performance

Journal Title: Computational Intelligence and Neuroscience
Year Published: 2022

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