Table of Contents

Statistics - Generalized Linear Models (GLM) - Extensions of the Linear Model

About

The Generalized Linear Model is an extension of the linear model that allows for lots of different, non-linear models to be tested in the context of regression.

GLM is the mathematical framework used in many statistical analyses such as:

GLM is a supervised algorithm with a classic statistical technique (Supports thousands of input variables, text and transactional data) used for:

GLM implements:

Confidence bounds are supported with a

Assumptions

The General Linear model has two main characteristics:

That doesn't mean that the GLM can't handle non-additive or non-linear effects.

Removing the additive assumption:

GLM can accommodate such non-additive or non-linear effects with:

Methods

Methods that expand the scope of linear models and how they are fit: