Negative binomial regression is used for modeling count variables, usually for over-dispersed count outcome variables (e.g. accounting for the extra-Poisson variation). BESH Stats fits negative binomial regression with the traditional NB2[1] parametrization
Category Archives: Counts data
Poisson regression (Generalized linear model GLM)
Poisson regression is fundamental to the modeling of count data. It is the simplest count regression model; and similar to regular multiple linear regression except that the dependent variable is an observed count that follows the Poisson distribution.