Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function

Detalhes bibliográficos
Autor(a) principal: Dey, Sanku
Data de Publicação: 2019
Outros Autores: Moala, Fernando Antonio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1108/IJQRM-01-2017-0012
http://hdl.handle.net/11449/185467
Resumo: Purpose The purpose of this paper is to deal with the Bayesian and non-Bayesian estimation methods of multicomponent stress-strength reliability by assuming the Chen distribution. Design/methodology/approach The reliability of a multicomponent stress-strength system is obtained by the maximum likelihood (MLE) and Bayesian methods and the results are compared by using MCMC technique for both small and large samples. Findings The simulation study shows that Bayes estimates based on gamma prior with absence of prior information performs little better than the MLE with regard to both biases and mean squared errors. The Bayes credible intervals for reliability are also shorter length with competitive coverage percentages than the condence intervals. Further, the coverage probability is quite close to the nominal value in all sets of parameters when both sample sizes n and m increases. Originality/value The lifetime distributions used in reliability analysis as exponential, gamma, lognormal and Weibull only exhibit monotonically increasing, decreasing or constant hazard rates. However, in many applications in reliability and survival analysis, the most realistic hazard rate is bathtub-shaped found in the Chen distribution. Therefore, the authors have studied the multicomponent stress-strength reliability under the Chen distribution by comparing the MLE and Bayes estimators.
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spelling Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate functionBayesian estimationMaximum likelihood estimationStress-strengthChen distributionReliability of multicomponentPurpose The purpose of this paper is to deal with the Bayesian and non-Bayesian estimation methods of multicomponent stress-strength reliability by assuming the Chen distribution. Design/methodology/approach The reliability of a multicomponent stress-strength system is obtained by the maximum likelihood (MLE) and Bayesian methods and the results are compared by using MCMC technique for both small and large samples. Findings The simulation study shows that Bayes estimates based on gamma prior with absence of prior information performs little better than the MLE with regard to both biases and mean squared errors. The Bayes credible intervals for reliability are also shorter length with competitive coverage percentages than the condence intervals. Further, the coverage probability is quite close to the nominal value in all sets of parameters when both sample sizes n and m increases. Originality/value The lifetime distributions used in reliability analysis as exponential, gamma, lognormal and Weibull only exhibit monotonically increasing, decreasing or constant hazard rates. However, in many applications in reliability and survival analysis, the most realistic hazard rate is bathtub-shaped found in the Chen distribution. Therefore, the authors have studied the multicomponent stress-strength reliability under the Chen distribution by comparing the MLE and Bayes estimators.St Anthony Coll, Dept Stat, Shillong, Meghalaya, IndiaUniv Estadual Paulista Portal, Dept Stat, Presidente Prudente, BrazilUniv Estadual Paulista Portal, Dept Stat, Presidente Prudente, BrazilEmerald Group Publishing LtdSt Anthony CollUniversidade Estadual Paulista (Unesp)Dey, SankuMoala, Fernando Antonio [UNESP]2019-10-04T12:35:41Z2019-10-04T12:35:41Z2019-02-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article122-136http://dx.doi.org/10.1108/IJQRM-01-2017-0012International Journal Of Quality & Reliability Management. Bingley: Emerald Group Publishing Ltd, v. 36, n. 2, p. 122-136, 2019.0265-671Xhttp://hdl.handle.net/11449/18546710.1108/IJQRM-01-2017-0012WOS:00045929510000116212695523666970000-0002-2445-0407Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal Of Quality & Reliability Managementinfo:eu-repo/semantics/openAccess2024-06-18T18:18:15Zoai:repositorio.unesp.br:11449/185467Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-18T18:18:15Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
title Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
spellingShingle Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
Dey, Sanku
Bayesian estimation
Maximum likelihood estimation
Stress-strength
Chen distribution
Reliability of multicomponent
title_short Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
title_full Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
title_fullStr Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
title_full_unstemmed Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
title_sort Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function
author Dey, Sanku
author_facet Dey, Sanku
Moala, Fernando Antonio [UNESP]
author_role author
author2 Moala, Fernando Antonio [UNESP]
author2_role author
dc.contributor.none.fl_str_mv St Anthony Coll
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Dey, Sanku
Moala, Fernando Antonio [UNESP]
dc.subject.por.fl_str_mv Bayesian estimation
Maximum likelihood estimation
Stress-strength
Chen distribution
Reliability of multicomponent
topic Bayesian estimation
Maximum likelihood estimation
Stress-strength
Chen distribution
Reliability of multicomponent
description Purpose The purpose of this paper is to deal with the Bayesian and non-Bayesian estimation methods of multicomponent stress-strength reliability by assuming the Chen distribution. Design/methodology/approach The reliability of a multicomponent stress-strength system is obtained by the maximum likelihood (MLE) and Bayesian methods and the results are compared by using MCMC technique for both small and large samples. Findings The simulation study shows that Bayes estimates based on gamma prior with absence of prior information performs little better than the MLE with regard to both biases and mean squared errors. The Bayes credible intervals for reliability are also shorter length with competitive coverage percentages than the condence intervals. Further, the coverage probability is quite close to the nominal value in all sets of parameters when both sample sizes n and m increases. Originality/value The lifetime distributions used in reliability analysis as exponential, gamma, lognormal and Weibull only exhibit monotonically increasing, decreasing or constant hazard rates. However, in many applications in reliability and survival analysis, the most realistic hazard rate is bathtub-shaped found in the Chen distribution. Therefore, the authors have studied the multicomponent stress-strength reliability under the Chen distribution by comparing the MLE and Bayes estimators.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-04T12:35:41Z
2019-10-04T12:35:41Z
2019-02-04
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 http://dx.doi.org/10.1108/IJQRM-01-2017-0012
International Journal Of Quality & Reliability Management. Bingley: Emerald Group Publishing Ltd, v. 36, n. 2, p. 122-136, 2019.
0265-671X
http://hdl.handle.net/11449/185467
10.1108/IJQRM-01-2017-0012
WOS:000459295100001
1621269552366697
0000-0002-2445-0407
url http://dx.doi.org/10.1108/IJQRM-01-2017-0012
http://hdl.handle.net/11449/185467
identifier_str_mv International Journal Of Quality & Reliability Management. Bingley: Emerald Group Publishing Ltd, v. 36, n. 2, p. 122-136, 2019.
0265-671X
10.1108/IJQRM-01-2017-0012
WOS:000459295100001
1621269552366697
0000-0002-2445-0407
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv International Journal Of Quality & Reliability Management
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 122-136
dc.publisher.none.fl_str_mv Emerald Group Publishing Ltd
publisher.none.fl_str_mv Emerald Group Publishing Ltd
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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