Bayesian Estimation of the Parameters of Bivariate Exponential Distributions

Abstract

In this article, we develop an empirical Bayesian approach for the Bayesian estimation of parameters in four bivariate exponential (BVE) distributions. We have opted for gamma distribution as a prior for the parameters of the model in which the hyper parameters have been estimated based on the method of moments and maximum likelihood estimates (MLEs). A simulation study was conducted to compute empirical Bayesian estimates of the parameters and their standard errors. We use moment estimators or MLEs to estimate the hyper parameters of the prior distributions. Furthermore, we compare the posterior mode of parameters obtained by different prior distributions and the Bayesian estimates based on gamma priors are very close to the true values as compared to improper priors. We use MCMC method to obtain the posterior mean and compared the same using the improper priors and the classical estimates, MLEs.

Keywords:

• Bayesian estimation
• Bivariate exponential
• Convergence sequence of Markov chain
• Gibbs sampling
• MCMC methods
• Simulation study

Mathematics Subject Classification:

• 62F15
• 62N02