Dependence analysis of rail power supply board based on conditional copula

In this paper, a model based on conditional copula is built to capture dependence in complex produces. Bivariate copula cannot describe the dependence of degradation which are also affected by other degradations, so an alternative method is based on conditional copula to capture co-dependency in degradation. Maximum likelihood estimate will be introduced to obtain the unknown parameters in models. In this paper, we consider two parametric families of copulas: Gaussian, Frank, Clayton, Gumbel. An application about power supply board will valid effectiveness of proposed model.