One‐inflation and unobserved heterogeneity in population size estimation  by Ryan T. Godwin | Zendy

Inan Gul | Zendy

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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.

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