Objective bayesian analysis for multiple repairable systems

被引：2

作者：

D'Andrea, Amanda M. E. ^{[1
]}

Tomazella, Vera L. D. ^{[1
]}

Aljohani, Hassan M. ^{[2
]}

Ramos, Pedro L. ^{[3
]}

Almeida, Marco P. ^{[1
,4
]}

Louzada, Francisco ^{[4
]}

Verssani, Bruna A. W. ^{[5
]}

Gazon, Amanda B. ^{[1
]}

Afify, Ahmed Z. ^{[6
]}

机构：

[1] Univ Fed Sao Carlos, Dept Stat, Sao Carlos, Brazil

[2] Taif Univ, Coll Sci, Dept Math & Stat, At Taif, Saudi Arabia

[3] Pontificia Univ Catolica Chile, Fac Matemat, Santiago, Chile

[4] Univ Sao Paulo, Inst Math & Comp Sci, Sao Carlos, Brazil

[5] Univ Sao Paulo, Dept Exact Sci, Piracicaba, Brazil

[6] Benha Univ, Dept Stat Math & Insurance, Banha, Egypt

来源：

PLOS ONE | 2021年 / 16卷 / 11期

关键词：

POWER-LAW PROCESSES; INFERENCE; DISTRIBUTIONS; INTENSITY; SELECTION; POLICIES; MODEL;

D O I：

10.1371/journal.pone.0258581

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This article focus on the analysis of the reliability of multiple identical systems that can have multiple failures over time. A repairable system is defined as a system that can be restored to operating state in the event of a failure. This work under minimal repair, it is assumed that the failure has a power law intensity and the Bayesian approach is used to estimate the unknown parameters. The Bayesian estimators are obtained using two objective priors know as Jeffreys and reference priors. We proved that obtained reference prior is also a matching prior for both parameters, i.e., the credibility intervals have accurate frequentist coverage, while the Jeffreys prior returns unbiased estimates for the parameters. To illustrate the applicability of our Bayesian estimators, a new data set related to the failures of Brazilian sugar cane harvesters is considered.

引用

页数：19

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