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Bayesian estimator for the total number of distinct species when quadrat sampling is used

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  • Sueli Mingoti

Abstract

A Bayesian estimator for the total number of distinct species present in the region of investigation is constructed when the quadrat sampling procedure is used to collect a sample of species. The estimator is based on a model similar to that used by Mingoti and Meeden, and uses as a special case the zero truncated negative binomial distribution as a prior distribution for the true number S of distinct species in the region. Confidence intervals are also obtained. Simple comparisons with the first-order jackknife estimator and the empirical Bayesian estimator are performed.

Suggested Citation

  • Sueli Mingoti, 1999. "Bayesian estimator for the total number of distinct species when quadrat sampling is used," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(4), pages 469-483.
    • Handle: RePEc:taf:japsta:v:26:y:1999:i:4:p:469-483
    DOI: 10.1080/02664769922359
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    Cited by:

    1. Sueli Mingoti, 2000. "A stepwise Bayesian estimator for the total number of distinct species in finite populations: Sampling by elements," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 651-670.
    2. Peter J. Haas & Yushan Liu & Lynne Stokes, 2006. "An Estimator of Number of Species from Quadrat Sampling," Biometrics, The International Biometric Society, vol. 62(1), pages 135-141, March.
    3. Jérôme A. Dupuis & Jean Joachim, 2006. "Bayesian Estimation of Species Richness from Quadrat Sampling Data in the Presence of Prior Information," Biometrics, The International Biometric Society, vol. 62(3), pages 706-712, September.
    4. Luana D'Alessandro & Lorenzo Fattorini, 2002. "Resampling estimators of specie richness from presence-absence data: why they don't work," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 3-17.
    5. Chang Dorea & Sueli Mingoti, 2006. "Estimating the total number of distinct species using quadrat sampling and under-dependence structure," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(5), pages 497-512.

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