Re-parameterization of multinomial distributions and diversity indices |
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Authors: | Zhiyi Zhang Jun Zhou |
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Affiliation: | Department of Mathematics and Statistics, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA |
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Abstract: | It is shown in this paper that the parameters of a multinomial distribution may be re-parameterized as a set of generalized Simpson's diversity indices. There are two important elements in the generalization: (1) Simpson's diversity index is extended to populations with infinite species; (2) weighting schemes are incorporated. A class of unbiased estimators for the generalized Simpson's biodiversity indices is proposed. Asymptotic normality is established for the estimators. Both the unbiasedness and the asymptotic normality of the estimators hold for all three cases of the number of species in the population: infinite, finite and known, and finite but unknown. In the case of a population with a finite number of species, known or unknown, it is also established that the proposed estimators are uniformly minimum variance unbiased and are asymptotically efficient. |
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Keywords: | Generalized Simpson's biodiversity indices Umvue Asymptotic normality Asymptotic efficiency |
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