Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/267548 |
Resumo: | In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes. |
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Louzada Neto, FranciscoCuminato, José AlbertoRodriguez, Oscar Mauricio HernandezTomazella, Vera Lucia DamascenoFerreira, Paulo HenriqueRamos, Pedro LutzMilani, Eder AngeloBochio, GustavoPerissini, Ivan CarlosGonzatto Junior, Oilson AlbertoMota, Alex LealAlegría, Luis Felipe AcunaColombo, DaniloPerondi, Eduardo AndréWentz, André ViegasSilva Junior, Anselmo Luís daBarone, Dante Augusto CoutoSantos, Hugo Francisco LisboaMagalhães, Marcus Vinicius de Campos2023-11-24T03:23:35Z20211932-6203http://hdl.handle.net/10183/267548001178049In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes.application/pdfengPloS one. San Francisco : Public Library of Science. Vol. 16, no. 8 (Ago. 2021), e0255944, 25 p.EstatísticaInferência bayesianaPoços de petróleoImproved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regimeEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001178049.pdf.txt001178049.pdf.txtExtracted Texttext/plain65200http://www.lume.ufrgs.br/bitstream/10183/267548/2/001178049.pdf.txt6c1f9c954a2ca2c2c6c2a1fc458c6e1eMD52ORIGINAL001178049.pdfTexto completo (inglês)application/pdf3354224http://www.lume.ufrgs.br/bitstream/10183/267548/1/001178049.pdfaee3dbcd55ce7d6eea61094d8731645cMD5110183/2675482023-12-06 04:24:29.071176oai:www.lume.ufrgs.br:10183/267548Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-12-06T06:24:29Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
title |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
spellingShingle |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime Louzada Neto, Francisco Estatística Inferência bayesiana Poços de petróleo |
title_short |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
title_full |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
title_fullStr |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
title_full_unstemmed |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
title_sort |
Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime |
author |
Louzada Neto, Francisco |
author_facet |
Louzada Neto, Francisco Cuminato, José Alberto Rodriguez, Oscar Mauricio Hernandez Tomazella, Vera Lucia Damasceno Ferreira, Paulo Henrique Ramos, Pedro Lutz Milani, Eder Angelo Bochio, Gustavo Perissini, Ivan Carlos Gonzatto Junior, Oilson Alberto Mota, Alex Leal Alegría, Luis Felipe Acuna Colombo, Danilo Perondi, Eduardo André Wentz, André Viegas Silva Junior, Anselmo Luís da Barone, Dante Augusto Couto Santos, Hugo Francisco Lisboa Magalhães, Marcus Vinicius de Campos |
author_role |
author |
author2 |
Cuminato, José Alberto Rodriguez, Oscar Mauricio Hernandez Tomazella, Vera Lucia Damasceno Ferreira, Paulo Henrique Ramos, Pedro Lutz Milani, Eder Angelo Bochio, Gustavo Perissini, Ivan Carlos Gonzatto Junior, Oilson Alberto Mota, Alex Leal Alegría, Luis Felipe Acuna Colombo, Danilo Perondi, Eduardo André Wentz, André Viegas Silva Junior, Anselmo Luís da Barone, Dante Augusto Couto Santos, Hugo Francisco Lisboa Magalhães, Marcus Vinicius de Campos |
author2_role |
author author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Louzada Neto, Francisco Cuminato, José Alberto Rodriguez, Oscar Mauricio Hernandez Tomazella, Vera Lucia Damasceno Ferreira, Paulo Henrique Ramos, Pedro Lutz Milani, Eder Angelo Bochio, Gustavo Perissini, Ivan Carlos Gonzatto Junior, Oilson Alberto Mota, Alex Leal Alegría, Luis Felipe Acuna Colombo, Danilo Perondi, Eduardo André Wentz, André Viegas Silva Junior, Anselmo Luís da Barone, Dante Augusto Couto Santos, Hugo Francisco Lisboa Magalhães, Marcus Vinicius de Campos |
dc.subject.por.fl_str_mv |
Estatística Inferência bayesiana Poços de petróleo |
topic |
Estatística Inferência bayesiana Poços de petróleo |
description |
In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021 |
dc.date.accessioned.fl_str_mv |
2023-11-24T03:23:35Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/267548 |
dc.identifier.issn.pt_BR.fl_str_mv |
1932-6203 |
dc.identifier.nrb.pt_BR.fl_str_mv |
001178049 |
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url |
http://hdl.handle.net/10183/267548 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
PloS one. San Francisco : Public Library of Science. Vol. 16, no. 8 (Ago. 2021), e0255944, 25 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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