A note on Bayesian inference for the bivariate pseudo-exponential model

Abstract

In this present work, we discuss the Bayesian inference for the Bivariate Pseudo-exponential distribution. Initially, we assume independent gamma priors and Pseudo-gamma priors for the Pseudo-exponential parameters. Possible conjugacy is investigated in both full and sub-models. In some special sub-cases, conjugate priors can be identified. We are primarily interested in deriving the posterior means for each prior assumed and comparing each of the posterior means with the maximum likelihood estimators. Finally, all the Bayesian analyses are illustrated with a simulation study to demonstrate the performance of Bayesian parameter estimates using a variety of informative and non-informative priors, also illustrated with real-life applications.