期刊
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
卷 47, 期 1, 页码 166-186出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2017.1280162
关键词
Bivariate degradation; Bayesian MCMC method; Copula function; Inverse Gaussian process; Random effects
资金
- National Natural Science Foundation of China [11671080]
- Innovation Project for College Graduates of Jiangsu Province of China [KYLX16_0183]
This article conducts a Bayesian analysis for bivariate degradation models based on the inverse Gaussian (IG) process. Assume that a product has two quality characteristics (QCs) and each of the QCs is governed by an IG process. The dependence of the QCs is described by a copula function. A bivariate simple IG process model and three bivariate IG process models with random effects are investigated by using Bayesian method. In addition, a simulation example is given to illustrate the effectiveness of the proposed methods. Finally, an example about heavy machine tools is presented to validate the proposed models.
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