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Ordinal regression models for zero-inflated and/or over-dispersed count data

Count data commonly arise in natural sciences but adequately modeling these data is challenging due to zero-inflation and over-dispersion. While multiple parametric modeling approaches have been proposed, unfortunately there is no consensus regarding how to choose the best model. In this article, we...

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Detalles Bibliográficos
Autores principales:	Valle, Denis, Ben Toh, Kok, Laporta, Gabriel Zorello, Zhao, Qing
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2019
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395857/ https://www.ncbi.nlm.nih.gov/pubmed/30816185 http://dx.doi.org/10.1038/s41598-019-39377-x

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