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Bayesian Estimation of Parameters of Augmenting Gamma Strength Reliability for Symmetric and Asymmetric Loss Functions |
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PP: 17-31 |
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doi:10.18576/jsap/060103
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Author(s) |
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N. Chandra,
V. K. Rathaur,
M. Pandey,
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Abstract |
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| This paper deals with the Bayesian and maximum likelihood estimation of augmented strength reliability Rk(k = 1,2,3) under Augmentation Strategy Plan (ASP).In Bayesian context we consider gamma prior for unknown parameters of augmented strength reliability model under squared error loss function (SELF)and linex loss function (LLF)for the generalized case of ASP.A Monte-Carlo importance sampling procedure has been implemented to approximate the Bayes and quasi-Bayes estimators of Rk. The performances of Bayes and quasi-Bayes estimators of augmented strength reliability under both the loss functions are compared with that of maximum likelihood estimators on the basis of their mean square errors and absolute biases. We analyze simulated and real data sets for illustrative purpose for validation of proposed estimators. |
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