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Estimating species richness by a Poisson-compound gamma model

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  • Ji-Ping Wang

Abstract

We propose a Poisson-compound gamma approach for species richness estimation. Based on the denseness and nesting properties of the gamma mixture, we fix the shape parameter of each gamma component at a unified value, and estimate the mixture using nonparametric maximum likelihood. A least-squares crossvalidation procedure is proposed for the choice of the common shape parameter. The performance of the resulting estimator of N is assessed using numerical studies and genomic data. Copyright 2010, Oxford University Press.

Suggested Citation

  • Ji-Ping Wang, 2010. "Estimating species richness by a Poisson-compound gamma model," Biometrika, Biometrika Trust, vol. 97(3), pages 727-740.
    • Handle: RePEc:oup:biomet:v:97:y:2010:i:3:p:727-740
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    File URL: http://hdl.handle.net/10.1093/biomet/asq026
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    Cited by:

    1. Li Zhang & Ying-Ying Zhang, 2022. "The Bayesian Posterior and Marginal Densities of the Hierarchical Gamma–Gamma, Gamma–Inverse Gamma, Inverse Gamma–Gamma, and Inverse Gamma–Inverse Gamma Models with Conjugate Priors," Mathematics, MDPI, vol. 10(21), pages 1-27, October.
    2. Seungchul Baek & Junyong Park, 2022. "A computationally efficient approach to estimating species richness and rarefaction curve," Computational Statistics, Springer, vol. 37(4), pages 1919-1941, September.
    3. repec:jss:jstsof:40:i09 is not listed on IDEAS
    4. Chee, Chew-Seng & Wang, Yong, 2016. "Nonparametric estimation of species richness using discrete k-monotone distributions," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 107-118.
    5. Chun-Huo Chiu & Yi-Ting Wang & Bruno A. Walther & Anne Chao, 2014. "An improved nonparametric lower bound of species richness via a modified good–turing frequency formula," Biometrics, The International Biometric Society, vol. 70(3), pages 671-682, September.
    6. Zhang, Hongmei & Ghosh, Kaushik & Ghosh, Pulak, 2012. "Sampling designs via a multivariate hypergeometric-Dirichlet process model for a multi-species assemblage with unknown heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2562-2573.

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