2001•Communications for Statistical Applications and MethodsRequires access

Bayes Estimators for Reliability of a k - Unit Standby System with Perfect Switch

Chang‐Soo Lee, Keeh Wan Kim, Young Min Park

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Abstract

Bayes estimators and generalized ML estimators for reliability of a k-unit hot standby system with the perfect switch based upon a complete sample of failure times observed from an exponential distribution using noninformative, generalized uniform, and gamma priors for the failure rate are proposed, and MSE`s of proposed several estimators for the standby system reliability are compared numerically each other through the Monte Carlo simulation.

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What this paper is about

Bayes estimators and generalized ML estimators for reliability of a k-unit hot standby system with the perfect switch based upon a complete sample of failure times observed from an exponential distribution using noninformative, generalized uniform, and gamma priors for the failure rate are proposed, and MSE`s of proposed several estimators for the standby system reliability are compared numerically each other through the Monte Carlo simulation.

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Available abstract

Bayes estimators and generalized ML estimators for reliability of a k-unit hot standby system with the perfect switch based upon a complete sample of failure times observed from an exponential distribution using noninformative, generalized uniform, and gamma priors for the failure rate are proposed, and MSE`s of proposed several estimators for the standby system reliability are compared numerically each other through the Monte Carlo simulation.

Key concepts: Estimator, Bayes' theorem, Prior probability, Reliability (semiconductor), Exponential distribution, Mathematics, Monte Carlo method, Statistics

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