Bayesian inference for hidden truncation Pareto (IV) models.

In this paper, we consider observations arising out from a hidden truncation Pareto (IV) distribution and to be used to make inferences about the inequality, precision, shape and truncation parameter(s). Two different types of dependent prior analyses are reviewed and compared with each other. We conjecture that mathematical tractability should be, perhaps, a minor consideration in choosing the appropriate choices of the hyper-parameters for the prior densities. Some illustrative examples are provided. A simulation study is conducted to illustrate the applicability of the proposed model. [ABSTRACT FROM AUTHOR]