Bayesian Reliability Analysis for Degradation Data Based on Stochastic Process Models
Author:
Affiliation:
1. Graduate School of Social Sciences, University of Hyogo
Publisher
The Institute of Systems, Control and Information Engineers
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/sss/2022/0/2022_124/_pdf
Reference17 articles.
1. [1] Singpurwalla, N. D., Survival in dynamic environments, Statistical Science, Vol.10, No.1, pp.86-103, 1995.
2. [2] Abdel-Hameed, M., Degradation process: an overview, Advanced in Degradation Modeling, Statistics for Industry and Technology, Nikulin, M. S., et.al. eds., pp.17-25 Birkhäuser, 2010.
3. [3] Kahle, W., Mercier, S. and Paroissin, C., Degradation Processes in Reliability, Wiley, 2016.
4. [4] Wang, X. and Xu, D., An inverse Gaussian process model for degradation data, Technometrics, Vol.52, No.2, pp.188-197, 2010.
5. [5] Padgett, W. J. and Tomlinson, M. A., Inference from accelerated degradation and failure data based on Gaussian process models, Lifetime Data Analysis, Vol.10, pp.191-206, 2004.
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