Bayesian estimation : Number of species from Poisson mixed exponential-gamma distribution using objective priors

Abstract

In this paper, we have considered the Poisson-exponential-gamma mixture model as a species problem. The classical estimation of the parameter has been proposed through profile and conditional likelihood methods. While in the Bayesian paradigm, Bernardo’s reference and Jeffery’s priors have been used to estimate the number of species. Although a Markov Chain Monte Carlo (MCMC) technique has been used for obtaining the Bayes estimates of the number of species parameter. The performances of the proposed estimators are compared in terms of their risks through the simulation study. The applicability, and suitability of the proposed model have been performed using Mount Kenya insect species data.