Generalized Linear Models

Generalized Linear Model (GLiM, or GLM) is an advanced statistical modelling technique formulated by John Nelder and Robert Wedderburn in 1972. It is an umbrella term that encompasses many other models, which allows the response variable y to have an error distribution other than a normal distribution. The models include Linear Regression, Logistic Regression, and Poisson Regression. The underlying relationship between the response and the predictors is linear (i.e. Also, the error distribution of the response variable should be normally distributed.