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

Author

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

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.

Suggested Citation

  • Leite, José G. & Rodrigues, Josemar & Milan, Luis A., 2000. "A Bayesian analysis for estimating the number of species in a population using nonhomogeneous Poisson process," Statistics & Probability Letters, Elsevier, vol. 48(2), pages 153-161, June.
    • Handle: RePEc:eee:stapro:v:48:y:2000:i:2:p:153-161
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    Cited by:

    1. Leonidas Sakalauskas, 2010. "On the Empirical Bayesian Approach for the Poisson-Gaussian Model," Methodology and Computing in Applied Probability, Springer, vol. 12(2), pages 247-259, June.
    2. Beverley Causey, 2002. "Parametric estimation of the number of classes in a population," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 925-934.

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