Nonparametric estimation of species richness using discrete \(k\)-monotone distributions

DOI10.1016/j.csda.2014.10.021zbMath1468.62036OpenAlexW1991913268MaRDI QIDQ1660193

Yong Wang, Chew-Seng Chee

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.10.021

zbMATH Keywords

nonparametric mixturespecies richnessunconditional maximum likelihooddiscrete \(k\)-monotone distributionshape-restricted estimation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items (10)

Testing convexity of a discrete distribution ⋮ 2nd special issue on robust analysis of complex data ⋮ Editorial: The third special issue on advances in mixture models ⋮ Testing \(k\)-monotonicity of a discrete distribution. Application to the estimation of the number of classes in a population ⋮ Completely monotone distributions: mixing, approximation and estimation of number of species ⋮ Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain ⋮ Multiple monotonicity of discrete distributions: the case of the Poisson model ⋮ Least squares estimation of a completely monotone pmf: from analysis to statistics ⋮ A computationally efficient approach to estimating species richness and rarefaction curve ⋮ Species abundance distribution and species accumulation curve: a general framework and results

Uses Software

• SPECIES

Cites Work

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• Estimating the Size of a Multinomial Population
• A Penalized Nonparametric Maximum Likelihood Approach to Species Richness Estimation
• Nonparametric Maximum Likelihood Estimation of Population Size Based on the Counting Distribution

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