Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://revstat.ine.pt/index.php/REVSTAT/article/view/544 |
Resumo: | In this article, we propose and study a new three-parameter heavy-tailed distribution that unifes the Burr type XII and power inverted Topp-Leone distributions in an original manner. This unification is made through the use of a simple 'shift parameter'. Among its interesting functionalities, it exhibits possibly decreasing and unimodal probability density and hazard rate functions. We examine its quantile function, stochastic dominance, ordinary moments, weighted moments, incomplete moments, and stress-strength reliability cofficient. Then, the classical and Bayesian approaches are developed to estimate the model and stress strength reliability parameters. Bayes estimates are obtained under the squared error and entropy loss functions. Simulated data are considered to point out the performance of the derived estimates based on the mean squared error. In the final part, the potential of the new model is exemplified by the analysis of two engineering data sets, showing that it is preferable to other reputable and comparable models. |
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Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023Burr distributionBayesian inferenceMaximum likelihood methodstress-strength reliabilitydata analysisIn this article, we propose and study a new three-parameter heavy-tailed distribution that unifes the Burr type XII and power inverted Topp-Leone distributions in an original manner. This unification is made through the use of a simple 'shift parameter'. Among its interesting functionalities, it exhibits possibly decreasing and unimodal probability density and hazard rate functions. We examine its quantile function, stochastic dominance, ordinary moments, weighted moments, incomplete moments, and stress-strength reliability cofficient. Then, the classical and Bayesian approaches are developed to estimate the model and stress strength reliability parameters. Bayes estimates are obtained under the squared error and entropy loss functions. Simulated data are considered to point out the performance of the derived estimates based on the mean squared error. In the final part, the potential of the new model is exemplified by the analysis of two engineering data sets, showing that it is preferable to other reputable and comparable models.Statistics Portugal2023-03-14info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://revstat.ine.pt/index.php/REVSTAT/article/view/544REVSTAT-Statistical Journal; new articleREVSTAT; new article2183-03711645-6726reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://revstat.ine.pt/index.php/REVSTAT/article/view/544https://revstat.ine.pt/index.php/REVSTAT/article/view/544/619Copyright (c) 2022 REVSTAT-Statistical Journalinfo:eu-repo/semantics/openAccessAgiwal, VarunTyagi, ShikharChesneau , Christophe2023-03-18T06:30:12Zoai:revstat:article/544Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:42:50.920199Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
title |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
spellingShingle |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 Agiwal, Varun Burr distribution Bayesian inference Maximum likelihood method stress-strength reliability data analysis |
title_short |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
title_full |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
title_fullStr |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
title_full_unstemmed |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
title_sort |
Bayesian and Frequentist Estimation of Stress-Strength Reliability from a New Extended Burr XII Distribution: Accepted: March 2023 |
author |
Agiwal, Varun |
author_facet |
Agiwal, Varun Tyagi, Shikhar Chesneau , Christophe |
author_role |
author |
author2 |
Tyagi, Shikhar Chesneau , Christophe |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Agiwal, Varun Tyagi, Shikhar Chesneau , Christophe |
dc.subject.por.fl_str_mv |
Burr distribution Bayesian inference Maximum likelihood method stress-strength reliability data analysis |
topic |
Burr distribution Bayesian inference Maximum likelihood method stress-strength reliability data analysis |
description |
In this article, we propose and study a new three-parameter heavy-tailed distribution that unifes the Burr type XII and power inverted Topp-Leone distributions in an original manner. This unification is made through the use of a simple 'shift parameter'. Among its interesting functionalities, it exhibits possibly decreasing and unimodal probability density and hazard rate functions. We examine its quantile function, stochastic dominance, ordinary moments, weighted moments, incomplete moments, and stress-strength reliability cofficient. Then, the classical and Bayesian approaches are developed to estimate the model and stress strength reliability parameters. Bayes estimates are obtained under the squared error and entropy loss functions. Simulated data are considered to point out the performance of the derived estimates based on the mean squared error. In the final part, the potential of the new model is exemplified by the analysis of two engineering data sets, showing that it is preferable to other reputable and comparable models. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-03-14 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revstat.ine.pt/index.php/REVSTAT/article/view/544 |
url |
https://revstat.ine.pt/index.php/REVSTAT/article/view/544 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revstat.ine.pt/index.php/REVSTAT/article/view/544 https://revstat.ine.pt/index.php/REVSTAT/article/view/544/619 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 REVSTAT-Statistical Journal info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 REVSTAT-Statistical Journal |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Statistics Portugal |
publisher.none.fl_str_mv |
Statistics Portugal |
dc.source.none.fl_str_mv |
REVSTAT-Statistical Journal; new article REVSTAT; new article 2183-0371 1645-6726 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131514935443456 |