Bayesian inference for a simple step-stress accelerated dependent competing failure model

Abstract

The Copula approach can be used to describe the dependence structure between variables. In this paper, by using a Bivariate Clayton copula, we discuss the statistical analysis of a simple step-stress accelerated dependent competing failure model under progressively Type-II censoring sample. With the assumption of cumulative exposure, the Bayesian estimations of the model parameters are derived. Based on Monte-Carlo simulation, the precision of the estimates is assessed. Finally, the statistical analysis of an actual data set of a solar lighting insulation system has been presented for illustrative purposes.