A class of bivariate models with proportional reversed hazard marginals

Recently the proportional reversed hazard model has received a considerable amount of attention in the statistical literature. The main aim of this paper is to introduce a bivariate proportional reversed hazard model and discuss its different properties. In most of the cases the joint probability distribution function can be expressed in compact forms. The maximum likelihood estimators cannot be expressed in explicit forms in most of the cases. EM algorithm has been proposed to compute the maximum likelihood estimators of the unknown parameters. For illustrative purposes two data sets have been analyzed and the performances are quite satisfactory.