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Parametric estimation of the number of classes in a population

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  • Beverley Causey

Abstract

This paper deals with the well-studied problem of how best to estimate the number of mutually exclusive and exhaustive classes in a population, based on a sample from it. Haas & Stokes review and provide non-parametric approaches, but there are associated difficulties especially for small sampling fractions and/or widely varying population class sizes. Sichel provided 'GIGP' methodology, for this problem and for other purposes; this paper utilizes the three-parameter GIGP distribution for this problem, and also for the estimation of the number of classes of size 1, as an alternative to the non-parametric approaches. Methodological and computational issues are considered, and examples indicate the potential for GIGP.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:29:y:2002:i:6:p:925-934
    DOI: 10.1080/02664760220136221
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    References listed on IDEAS

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    1. 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.
    2. B.V. Greenberg & L.V. Zayatz, 1992. "Strategies for measuring risk in public use microdata files," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 46(1), pages 33-48, March.
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