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

Biom J. 2018 Jul;60(4):859-864. doi: 10.1002/bimj.201700261. Epub 2018 May 11.

Abstract

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.

Keywords: count data; mean parameterization; one-inflation; zero-truncation.

Publication types

  • Letter

MeSH terms

  • Binomial Distribution
  • Biometry / methods*
  • Humans
  • Opioid-Related Disorders / epidemiology
  • Poisson Distribution