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Improved objective Bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime.
Louzada, Francisco; Cuminato, José A; Rodriguez, Oscar M H; Tomazella, Vera L D; Ferreira, Paulo H; Ramos, Pedro L; Milani, Eder A; Bochio, Gustavo; Perissini, Ivan C; Gonzatto Junior, Oilson A; Mota, Alex L; Alegría, Luis F A; Colombo, Danilo; Perondi, Eduardo A; Wentz, André V; Júnior, Anselmo L Silva; Barone, Dante A C; Santos, Hugo F L; Magalhães, Marcus V C.
Afiliação
  • Louzada F; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Cuminato JA; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Rodriguez OMH; School of Engineering (EESC), University of São Paulo, São Carlos, SP, Brazil.
  • Tomazella VLD; Department of Statistics (DEs), Federal University of São Carlos, São Carlos, SP, Brazil.
  • Ferreira PH; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Ramos PL; Department of Statistics (DEst), Federal University of Bahia, Salvador, BA, Brazil.
  • Milani EA; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Bochio G; Pontificia Universidad Católica de Chile, Facultad de Matemáticas, Macul, Santiago, Chile.
  • Perissini IC; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Gonzatto Junior OA; Institute of Mathematics and Statistics (IME), Federal University of Goiás, Goiânia, GO, Brazil.
  • Mota AL; School of Engineering (EESC), University of São Paulo, São Carlos, SP, Brazil.
  • Alegría LFA; School of Engineering (EESC), University of São Paulo, São Carlos, SP, Brazil.
  • Colombo D; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Perondi EA; Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, SP, Brazil.
  • Wentz AV; School of Engineering (EESC), University of São Paulo, São Carlos, SP, Brazil.
  • Júnior ALS; Leopoldo Américo Miguez de Mello Research and Development Center (CENPES-Petrobras), Rio de Janeiro, RJ, Brazil.
  • Barone DAC; Department of Mechanical Engineering, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil.
  • Santos HFL; National Service of Industrial Training (SENAI), São Leopoldo, RS, Brazil.
  • Magalhães MVC; National Service of Industrial Training (SENAI), Florianópolis, SC, Brazil.
PLoS One ; 16(8): e0255944, 2021.
Article em En | MEDLINE | ID: mdl-34383829
ABSTRACT
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil