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

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.

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Year of publication:	2000
Authors:	Leite, José G. ; Rodrigues, Josemar ; Milan, Luis A.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 48.2000, 2, p. 153-161
Publisher:	Elsevier
Keywords:	[pi]-mixture Bayesian estimator Empirical Bayes estimator Exponential model Prior and posterior distributions Metropolis-within-Gibbs

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005319692