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

Gül Inan
Published in: Biometrical journal. Biometrische Zeitschrift (2018)
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.
Keyphrases
  • primary care
  • machine learning
  • single cell
  • deep learning