Objective bayesian analysis for recurrent events in presence of competing risks

In this article, we use Bayesian reference analysis to consider the model of recurrent events with competing risks, where the sampling distribution of the observations due to some failure types is modeled through a proportional intensity homogeneous Poisson process and individuals are expected to experience repeated events along with the fixed covariates. The goal is to estimate the cause-specific intensity functions. Three reference priors are derived according to this model. Their associated posteriors are also discussed. The simulation work and real data application based on the reference priors and the classical likelihood approach show the efficiency of reference analysis.