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Statistical Methods for Overdispersed Count Data

  • 1 Edición - 19 de noviembre de 2018
  • Última edición
  • Autor: Jean-Francois Dupuy
  • Idioma: Inglés

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages… Leer más

Descripción

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementation. All methods are illustrated on datasets arising in the field of health economics. As several tools have been developed to tackle over-dispersed and zero-inflated data (such as adjustment methods and zero-inflated models), this book covers the topic in a comprehensive and interesting manner.

Puntos claves

  • Includes reading on several levels, including methodology and applications
  • Presents the state-of-the-art on the most recent zero-inflated regression models
  • Contains a single dataset that is used as a common thread for illustrating all methodologies
  • Includes R code that allows the reader to apply methodologies

De interès para

Students in statistics, biostatistics, econometrics and professional statisticians with interest in the analysis of count data; Non-statisticians with skills in R softwares (e.g. economists, decision-makers in public health)

Índice

1. A Brief Overview of Linear Models

2. Generalized Linear Models

3. Overdispersion in Count Data

4. Count Data and Zero Inflation

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 19 de noviembre de 2018
  • Idioma: Inglés

Sobre el autor

JD

Jean-Francois Dupuy

Jean-Francois Dupuy is a Professor at the INSA Rennes since 2011. From 2009 to 2011, he was a Professor at the University La Rochelle in France. In 2002 he obtained a PhD in Applied Mathematics from the University Paris-Descartes.
Afiliaciones y experiencia
INSA Rennes, France

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