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- W2977929382 abstract "In accelerated life test,some test data may be missed or not observed because of the test equipment or observation difficulty.A Bayesian method,which can appropriately utilize information coming from multiple sources,is proposed to solve the problem of reliability assessment for Weibull distribution products with small sampled missing data in constant-stress accelerated tests.Firstly,the likelihood function of the missing data is obtained by use of probability atom method.At the same time,the prior distribution of the unknown parameters in the likelihood function is set up according to their physics meaning.The super-parameters in the prior distribution functions can be estimated by the second Maximum Likelihood Estimation(ML-II) method.In the end A Monte Carlo study of the bias and mean square error of the estimators and a comparison with the properties of maximum likelihood estimators are carried out." @default.
- W2977929382 created "2019-10-10" @default.
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- W2977929382 date "2008-01-01" @default.
- W2977929382 modified "2023-09-26" @default.
- W2977929382 title "Bayesian reliability assessment based on constant-stress accelerated life testing for long-life products with Weibull Distribution when missing data" @default.
- W2977929382 hasPublicationYear "2008" @default.
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