Double Generalized Linear Models: Likelihood and Bayesian Methods

Provides an introduction to double generalized linear models (DGLMs), under frequentist and Bayesian frameworks.

Edilberto Cepeda-Cuervo has been a full professor of statistics at Universidad Nacional de Colombia (UNAL) in Bogotá, Colombia since 2004. He holds a Bachelor’s Degree in Physics and Mathematics from Universidad Libre de Colombia (1981); M.Sc. in Mathematics from Universidad de los Andes de Colombia (1983); and a Ph.D. in Mathematics from UFRJ (2001). He has been a full professor in the Statistics department of Universidad Nacional de Colombia since 2004.

He has authored or co-authored more than 60 scientific articles in the areas of generalized linear models, nonlinear regression, beta and gamma regression models, longitudinal data analysis, spatial statistics, overdispersion regression models and in interdisciplinary topics. These papers have been published in many statistical journals including Brazilian Journal of Probability and Statistics, Journal of Educational and Behavioral Statistics, Biometrical Journal, Journal of Applied Statistics and Computational Statistics.

Some research lines of interest are generalized linear models, double generalized linear models, overdispersion models, Bayesian statistics, longitudinal data analysis, and spatial econometrics.