Brazilian Journal of Probability and Statistics

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

Rodrigo Citton P. dos Reis, Enrico A. Colosimo, and Gustavo L. Gilardoni

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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.

Article information

Braz. J. Probab. Stat., Volume 33, Number 2 (2019), 374-396.

Received: July 2015
Accepted: January 2018
First available in Project Euclid: 4 March 2019

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Bootstrap correction maximum a posterior density minimal repair multiple repairable systems rejection sampling reliability


dos Reis, Rodrigo Citton P.; Colosimo, Enrico A.; Gilardoni, Gustavo L. Hierarchical modelling of power law processes for the analysis of repairable systems with different truncation times: An empirical Bayes approach. Braz. J. Probab. Stat. 33 (2019), no. 2, 374--396. doi:10.1214/18-BJPS393.

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