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:: Volume 14, Issue 2 (2-2021) ::
JSS 2021, 14(2): 549-564 Back to browse issues page
A Class of Bayesian Shrinkage Estimators for the Scale Parameter of Weibull Distribution Based on Censored Data
Mehran Naghizadeh Qomi *
Abstract:   (3825 Views)
In classical statistics, the parameter of interest is estimated based on sample information and using natural estimators such as maximum likelihood estimators. In Bayesian statistics, the Bayesian estimators are constructed based on prior knowledge and combining with it sample information. But, in some situations, the researcher has information about the unknown parameter as a guess. Bayesian shrinkage estimators can be constructed by Combining this non-sample information with sample information together with the prior knowledge, which is in the area of semi-classical statistics. In this paper, we introduce a class of Bayesian shrinkage estimators for the Weibull scale parameter as a generalization of the estimator at hand and consider the bias and risk of them under LINEX loss function. Then, the proposed estimators are compared using a real data set. 
Keywords: LINEX Loss Function, Weibull Distribution, Bayesian Shrinkage Estimator, Censored Data.
Full-Text [PDF 376 kb]   (1582 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2019/03/13 | Accepted: 2020/05/28 | Published: 2021/02/28
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Naghizadeh Qomi M. A Class of Bayesian Shrinkage Estimators for the Scale Parameter of Weibull Distribution Based on Censored Data. JSS 2021; 14 (2) :549-564
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 2 (2-2021) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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