A Note on Bayesian Inference for the Bivariate Pseudo-Exponential Data

TL;DR

This paper explores Bayesian inference methods for the bivariate pseudo-exponential distribution, comparing different priors and illustrating the approaches with simulations and real data.

Contribution

It introduces Bayesian inference techniques for the bivariate pseudo-exponential distribution using gamma and pseudo-gamma priors, with posterior mean derivations and comparisons.

Findings

Posterior means are derived for different priors.

Bayesian estimates are compared with maximum likelihood estimators.

Simulation and real data applications demonstrate the methods.

Abstract

In this present work, we discuss the Bayesian inference for the bivariate pseudo-exponential distribution. Initially, we assume independent gamma priors and then pseudo-gamma priors for the pseudo-exponential parameters. We are primarily interested in deriving the posterior means for each of the priors assumed and also comparing each of the posterior means with the maximum likelihood estimators. Finally, all the Bayesian analyses are illustrated with a simulation study and also illustrated with real-life applications.