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One-inflation and unobserved heterogeneity in population size estimation by Ryan T. Godwin.
Inan, Gul.
Afiliação
  • Inan G; Department of Statistics, Middle East Technical University, Ankara, 06800, Turkey.
Biom J ; 60(4): 859-864, 2018 07.
Article em En | MEDLINE | ID: mdl-29749022
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biometria Limite: Humans Idioma: En Revista: Biom J Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Turquia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biometria Limite: Humans Idioma: En Revista: Biom J Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Turquia