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

Francisco Louzada, José A Cuminato, Oscar M H Rodriguez, Vera L D Tomazella, Paulo H Ferreira, Pedro L Ramos, Eder A Milani, Gustavo Bochio, Ivan C Perissini, Oilson A Gonzatto Junior, Alex L Mota, Luis F A Alegría, Danilo Colombo, Eduardo A Perondi, André V Wentz, Anselmo L Silva Júnior, Dante A C Barone, Hugo F L Santos and Marcus V C Magalhães

PLOS ONE, 2021, vol. 16, issue 8, 1-25

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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0255944

DOI: 10.1371/journal.pone.0255944

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