Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第53回ISCIE「確率システム理論と応用」国際シンポジウム(2021年10月, 草津)
Bayesian Reliability Analysis for Degradation Data Based on Stochastic Process Models
Toru Kaise
著者情報
ジャーナル フリー

2022 年 2022 巻 p. 124-128

詳細
抄録
The stochastic process models are treated to estimate reliability assessments for degradation phenomena. In particular, the geometric Brownian motion and the gamma process models are handled, and the Bayesian procedures are applied to the models with the Markov chain Monte Carlo method. In addition, the estimation methods based on the empirical Bayesian, the maximum likelihood, and the generalized moment are also appropriated to the models. The information criterion EIC is used to select a fitted model among the stochastic models with the estimation procedures. The marginal likelihood with the Laplace’s method plays important roles in the methodologies proposed in this paper. In this paper, the Bayesian method with prior distributions is emphasized to apply expert opinions based on engineers for the reliability analysis. It is proposed that an expert opinion adopted to the analyzed phenomenon is chosen by using the information criterion EIC.
著者関連情報
© 2022 ISCIE Symposium on Stochastic Systems Theory and Its Applications
前の記事 次の記事
feedback
Top