Multivariate storage degradation modeling based on copula function

A generalized statistical model is introduced in the paper to qualify the reliability of a dormant system which has multiple de-pendent performance characteristics (PCs). In the model, the univariate degradation process of each PC is governed by Wiener processes with time transformation, and multivariate copula function is used to describe the dependence among the PCs. The parameters of Wiener process and copula function in the model are supposed to depend on temperature and their relationship can be expressed by the transformation functions. Based on the CSADT data, the parameters in the model can be calculated by the maximum likelihood estimate. Then the transformation functions can be derived from these estimated values by the regression analysis. Particularly, as the storage temperature is not constant, the variation of the temperature is taken into consideration in the model. In the end, as an illustration for the given model, a case application is presented as an example.