Improved objective bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime

Detalhes bibliográficos
Autor(a) principal: Louzada Neto, Francisco
Data de Publicação: 2021
Outros Autores: 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
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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spelling 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
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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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dc.language.iso.fl_str_mv eng
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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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eu_rights_str_mv openAccess
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