Nonparametric estimation of species richness using discrete k-monotone distributions

Chew-Seng Chee and Yong Wang

Computational Statistics & Data Analysis, 2016, vol. 93, issue C, 107-118

Abstract: Nonparametric mixture models are commonly used to estimate the number of unobserved species for their robustness of modelling heterogeneity. In particular, Poisson mixtures are popular in this regard, but they are also known to have the boundary problem that causes unstable estimation. A family of shape-restricted distributions known as discrete k-monotone distributions is proposed for species richness estimation. These distributions are in fact also nonparametric mixtures and can thus be fitted rapidly via some algorithms that are made available recently. As shown by empirical studies, as compared with Poisson mixtures, their use avoids the boundary problem and gives more stable and more accurate estimates.

Keywords: Discrete k-monotone distribution; Nonparametric mixture; Shape-restricted estimation; Species richness; Unconditional maximum likelihood (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:93:y:2016:i:c:p:107-118

DOI: 10.1016/j.csda.2014.10.021

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