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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10681

Title: Reliability estimation based on general progressive censored data from the Weibull model: comparison between Bayesian and classical approaches
Authors: Sultan, KS
Keywords: Two-parameter Weibull model
Type-II general progressive censoring
Bayesian estimation; maximum likelihood estimates
Bivariate prior; Noninformative prior;
Monte Carlo simulation experiments;
Estimated risk and mean squared error.
Relative efficiency
Issue Date: 2005
Publisher: Quality Technology & Quantitative Management
Citation: Vol. 2, No. 2, pp. 161-175, 2005 QTQM
Abstract: Inthis article, we consider the problem of estimating the parameters and reliability function of the two-parameter Weibull model on the basis of a progressive Type-II censored sample. We consider both classical and Bayesian approaches. In the Bayesian framework, we suggest a bivariate prior density for the two unknown parameters. Assuming the squared error loss function, we derive exact forms of the Bayes estimates. Further, we consider non-informative priors. To assess the accuracy of the resulting estimates, we conduct simulation experiments. In such experiments, we calculate the estimated risks (ER’s) and mean squared errors (MSE’s) of the Bayes estimates and compare them with the corresponding mean squared errors (MSE’s) of the maximum likelihood estimates. In addition, we calculate the relative efficiency between the considered estimates. Finally, we draw some concluding remarks.
URI: http://hdl.handle.net/123456789/10681
Appears in Collections:College of Science

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