Bayes Estimators for Reliability of a k - Unit Standby System with Perfect Switch
Chang‐Soo Lee, Keeh Wan Kim, Young Min Park
Abstract
Chang‐Soo Lee, Keeh Wan Kim, Young Min Park
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.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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