On estimation of the Poisson parameter in zero-modified Poisson models

By E. Dietz, Dankmar Böhning. 2000

124 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b92091b90536c72b7be1d86315f7445cb8a9d744

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In Artificial Intelligence

In Statistics and Probability

Citations in the corpus

Nonparametric maximum likelihood estimation of population size based on the counting distribution (2005, methodology): “The data are taken from Thyrion (1960) and have been used on various occasions in the literature, including Böhning (2000) and Carlin and Louis (1996). ni represents the frequency of accident policies reporting exactly i claims.”
Zero‐Inflated Negative Binomial Mixed Regression Modeling of Over‐Dispersed Count Data with Extra Zeros (2003, unknown): “A class of zero-modified Poisson models is discussed in Dietz and Böhning (2000).”
Point and interval estimation of the population size using the truncated Poisson regression model (2003, methodology): “An alternative method that employs the EM-algorithm is proposed by Dietz and Böhning (2000).”
The misuse of the Vuong test for non-nested models to test for zero-inflation (2015, unknown): “Dietz and Böhning (2000) proposed a link function that allowed for zerodeflation, and more recently Todem, Hsu and Kim (2012) have proposed a score test that incorporates a link function that allows for both zeroinflation and deflation.”
Finite Mixture, Zero-inflated Poisson and Hurdle models with application to SIDS (2003, result): “This results in a more accurate analysis, with a more comprehensive understanding of the relationship between SIDS and climate.”
Score Test for Zero Inflated Generalized Poisson Regression Model (2005, methodology): “In the literature several authors have analyzed such data sets by the use of zero inflated Poisson, negative binomial or binomial models; see Bohning et al. (1999), Dietz and Bohning (2000), Gupta et al. (1996), Ridout et al. (2001), Van den Broek (1995) and the references therein.”
Two‐part regression models for longitudinal zero‐inflated count data (2010, methodology): “The problem of zero inflation in count data has a long history in the statistical literature (see, e.g., Dietz & Böhning, 2000 and references therein) and several competing models have been proposed (see, e.g., Nikoloupoulos & Karlis, 2008; Greene, 2009).”