Introduction
What this guide covers
A comprehensive mathematical exposition of GLMs, from the internal geometry of the exponential family of dispersion and iterative estimation by IRLS, to asymptotic hypothesis testing, residual analysis and quasi-likelihood.
Overview
Topics covered
- Introduction
- Generalized Linear Models: Inference and Comparison
- Fundamentals and Theoretical Introduction
- Limitations of the Classical Linear Model
- Definition and Three Components of the GLM
- 1. The Random Component
Related concepts
Main connections
Compatible notation
Mathematical sample in LaTeX
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\mathbf{y} = \mathbf{X}\boldsymbol{\beta} + \boldsymbol{\epsilon}