Nonparametric maximum likelihood estimation of population size based on the counting distribution

72 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A covariate adjustment for zero-truncated approaches to estimating the size of hidden and elusive populations (2009, methodology): “(2003a), van der Heijden, Cruyff and van Houwelingen (2003b), Böhning and Schön (2005)], so that a strong disagreement of the homogeneous Poisson estimate to the Zelterman estimate might be taken as an indication for a lack of fit for the homogeneous Poisson as occurs here.”
Estimating the Number of Species in Microbial Diversity Studies (2014, background): “Estimators developed under the assumption of homogeneity, i.e., equal species abundances (λi ≡ λ), are well known to be biased significantly downward in the presence of heterogeneity, i.e., unequal species abundances (Böhning & Schön 2005).”
Two‐part regression models for longitudinal zero‐inflated count data (2010, methodology): “Rather than performing a complete convergence cycle within each E-step, we decided, according to Böhning & Schön (2005), to calculate n̂0 (and the weightsw∗ik) only once within each E-step, looking for global convergence.”