Usage of GLM

You can use generalized linear model (GLM) to handle heavy-tailed distributions and nominal (discrete-valued) distributions. GML can model non-linear relationships, while a set of diverse distributions is allowed for the response variable.

You can apply GLM in different areas, such as biology, biopharmaceuticals, engineering, actuarial science, and quality assurance.

Assume that you have a set of records, each of which is describing an event that is independent of the other events. Each event has a response variable and a set of predictor variables. The goal of GLM is to find a model that you can use to predict the value of the response variable based on the known values of the predictor variables.