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Bayesian estimation of Rayleigh distribution in the presence of outliers using progressive censoring
2020
Journal:  
Hacettepe Journal of Mathematics and Statistics
Author:  
Abstract:

In this article, Maximum likelihood estimation (MLE) and Bayesian estimation for Rayleigh distribution using progressive type-II censoring in the presence of outliers is considered. Inverse Gamma prior and Jeffreys prior are used for Bayesian estimation. Squared error loss function (SELF), precautionary loss function (PLF) and K-loss function (KLF) are used for obtaining the expressions of Bayes estimators and posterior risks. Credible intervals are also derived. A simulation study is presented to discuss the behavior of Bayes estimators. Applicability of the undertaken study is highlighted using three real data sets.

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2020
Author:  
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Hacettepe Journal of Mathematics and Statistics

Field :   Fen Bilimleri ve Matematik

Journal Type :   Uluslararası

Metrics
Article : 1.771
Cite : 682
2023 Impact : 0.004
Hacettepe Journal of Mathematics and Statistics