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E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme

In this paper, E-Bayesian estimation of the scale parameter, reliability and hazard rate functions of Chen distribution are considered when a sample is obtained from a type-I censoring scheme. The E-Bayesian estimators are obtained based on the balanced squared error loss function and using the gamm...

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Autores principales: Algarni, Ali, Almarashi, Abdullah M., Okasha, Hassan, Ng, Hon Keung Tony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517171/
https://www.ncbi.nlm.nih.gov/pubmed/33286408
http://dx.doi.org/10.3390/e22060636
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author Algarni, Ali
Almarashi, Abdullah M.
Okasha, Hassan
Ng, Hon Keung Tony
author_facet Algarni, Ali
Almarashi, Abdullah M.
Okasha, Hassan
Ng, Hon Keung Tony
author_sort Algarni, Ali
collection PubMed
description In this paper, E-Bayesian estimation of the scale parameter, reliability and hazard rate functions of Chen distribution are considered when a sample is obtained from a type-I censoring scheme. The E-Bayesian estimators are obtained based on the balanced squared error loss function and using the gamma distribution as a conjugate prior for the unknown scale parameter. Also, the E-Bayesian estimators are derived using three different distributions for the hyper-parameters. Some properties of E-Bayesian estimators based on balanced squared error loss function are discussed. A simulation study is performed to compare the efficiencies of different estimators in terms of minimum mean squared errors. Finally, a real data set is analyzed to illustrate the applicability of the proposed estimators.
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spelling pubmed-75171712020-11-09 E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme Algarni, Ali Almarashi, Abdullah M. Okasha, Hassan Ng, Hon Keung Tony Entropy (Basel) Article In this paper, E-Bayesian estimation of the scale parameter, reliability and hazard rate functions of Chen distribution are considered when a sample is obtained from a type-I censoring scheme. The E-Bayesian estimators are obtained based on the balanced squared error loss function and using the gamma distribution as a conjugate prior for the unknown scale parameter. Also, the E-Bayesian estimators are derived using three different distributions for the hyper-parameters. Some properties of E-Bayesian estimators based on balanced squared error loss function are discussed. A simulation study is performed to compare the efficiencies of different estimators in terms of minimum mean squared errors. Finally, a real data set is analyzed to illustrate the applicability of the proposed estimators. MDPI 2020-06-08 /pmc/articles/PMC7517171/ /pubmed/33286408 http://dx.doi.org/10.3390/e22060636 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Algarni, Ali
Almarashi, Abdullah M.
Okasha, Hassan
Ng, Hon Keung Tony
E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme
title E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme
title_full E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme
title_fullStr E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme
title_full_unstemmed E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme
title_short E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme
title_sort e-bayesian estimation of chen distribution based on type-i censoring scheme
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517171/
https://www.ncbi.nlm.nih.gov/pubmed/33286408
http://dx.doi.org/10.3390/e22060636
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