Hierarchical modelling of power law processes for the analysis of repairable systems with different truncation times: An empirical Bayes approach

被引：3
|
作者：
dos Reis, Rodrigo Citton P. [1 ]
Colosimo, Enrico A. [2 ]
Gilardoni, Gustavo L. [3 ]
机构：
[1] Univ Fed Rio Grande do Sul, Dept Estat, BR-91509900 Porto Alegre, RS, Brazil
[2] Univ Fed Minas Gerais, Dept Estat, BR-31270901 Belo Horizonte, MG, Brazil
[3] Univ Brasilia, Dept Estat, BR-70910900 Brasilia, DF, Brazil
来源：
BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS | 2019年 / 33卷 / 02期
关键词：
Bootstrap correction; maximum a posterior density; minimal repair; multiple repairable systems; rejection sampling; reliability; OPTIMAL MAINTENANCE TIME; CONFIDENCE-INTERVALS; POISSON-PROCESS; INFERENCE; RELIABILITY;
D O I：
10.1214/18-BJPS393
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In the data analysis from multiple repairable systems, it is usual to observe both different truncation times and heterogeneity among the systems. Among other reasons, the latter is caused by different manufacturing lines and maintenance teams of the systems. In this paper, a hierarchical model is proposed for the statistical analysis of multiple repairable systems under different truncation times. A reparameterization of the power law process is proposed in order to obtain a quasi-conjugate bayesian analysis. An empirical Bayes approach is used to estimate model hyperparameters. The uncertainty in the estimate of these quantities are corrected by using a parametric bootstrap approach. The results are illustrated in a real data set of failure times of power transformers from an electric company in Brazil.
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页码：374 / 396
页数：23
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