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One‐inflation and unobserved heterogeneity in population size estimation by Ryan T. Godwin
Author(s) -
Inan Gul
Publication year - 2018
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201700261
Subject(s) - negative binomial distribution , statistics , econometrics , mathematics , inflation (cosmology) , regression analysis , binomial regression , regression , feature (linguistics) , logistic regression , zero (linguistics) , population , poisson distribution , demography , sociology , philosophy , linguistics , physics , theoretical physics
In this study, we would like to show that the one‐inflated zero‐truncated negative binomial (OIZTNB) regression model can be easily implemented in R via built‐in functions when we use mean‐parameterization feature of negative binomial distribution to build OIZTNB regression model. From the practitioners' point of view, we believe that this approach presents a computationally convenient way for implementation of the OIZTNB regression model.