One-inflation and unobserved heterogeneity in population size estimation by Ryan T. Godwin

Date

2018-07-01

Author

İnan, Gül

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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.

Subject Keywords

Count data, Mean parameterization, One-inflation, Zero-truncation

URI

https://hdl.handle.net/11511/57273

Journal

BIOMETRICAL JOURNAL

DOI

https://doi.org/10.1002/bimj.201700261

Collections

Department of Statistics, Article

Citation Formats

G. İnan, “One-inflation and unobserved heterogeneity in population size estimation by Ryan T. Godwin,” BIOMETRICAL JOURNAL, vol. 60, no. 4, pp. 859–864, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57273.