WORKSHOP ON RISK ANALYSIS AND APPLICATIONS
24 and 25 of SEPTEMBER, 2025
Institute of Mathematics and, Statistics of the University of São Paulo, Brazil
SATELLITE WORKSHOP OF
8th BRAZILIAN CONFERENCE ON STATISTICAL MODELING IN INSURANCE AND FINANCE
WORKSHOP ON RISK ANALYSIS AND APPLICATIONS
24 and 25 of SEPTEMBER, 2025
Institute of Mathematics and, Statistics of the University of São Paulo, Brazil
SATELLITE WORKSHOP OF
8th BRAZILIAN CONFERENCE ON STATISTICAL MODELING IN INSURANCE AND FINANCE
Title: Bayesian Inference for Partial Imperfect Repair Models
In this talk, we focus on Bayesian inference for Partial Imperfect Repair models, a class of models designed to evaluate the reliability of repairable systems under partial imperfect maintenance scenarios. Our primary goal is to estimate the parameters of PIR models using Bayesian methods, emphasizing the role of prior distributions and their influence on the inferential process. We develop and implement Bayesian approaches tailored for repairable systems, comparing their performance against classical methods through Monte Carlo simulations. These comparisons aim to highlight the advantages of the Bayesian framework, particularly in terms of parameter estimation accuracy and computational efficiency. Finally, we demonstrate the applicability of the proposed Bayesian models by addressing relevant case studies in repairable systems, showcasing the practical implications and insights derived from this methodology.