Regression Models

Abstract

The aim of regression models is to model the variation of a quantitative response variable y in terms of the variation of one or several explanatory variables (x1, …, xp)⊤. We have already introduced such models in Chaps. 3and 7where linear models were written in (3.50) as $$\displaystyle{y = \mathcal{X}\beta +\varepsilon,}$$where y(n × 1) is the vector of observation for the response variable, $$\mathcal{X}(n \times p)$$is the data matrix of the p explanatory variables and $$\varepsilon$$are the errors.