A Bayesian analysis for estimating the number of species in a population using nonhomogeneous Poisson process

José G. Leite, Josemar Rodrigues and Luis A. Milan

Statistics & Probability Letters, 2000, vol. 48, issue 2, 153-161

Abstract: We propose a Bayesian approach using nonhomogeneous Poisson process to estimate the number of species of a population. The proposed methodology uses a [pi]-mixture to eliminate the unknown total mean of each species. One contribution of the article is to apply the Metropolis-within-Gibbs algorithm to obtain the marginal posterior distribution of the number of species and the capture mean time.

Keywords: [pi]-mixture; Bayesian; estimator; Empirical; Bayes; estimator; Exponential; model; Prior; and; posterior; distributions; Metropolis-within-Gibbs (search for similar items in EconPapers)
Date: 2000
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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