Linear Models with Heterogeneous Variance

Abstract

In this chapter, we review the theory of the classical linear models (LMs), suitable to analyze data involving independent observations with a homogeneous variance. In Sects. 4.3 and 4.4, we introduce the specification of the model. Estimation methods are discussed in Sect. 4.4. Section 4.5 offers a review of the diagnostic methods, while in Sect. 4.6, we describe the inferential tools available for the model. In Sect. 4.7, we summarize strategies that can be followed in order to reduce a model or to select one model from a set of several competing ones. The implementation of the theoretical concepts and methods for the classical LMs in R will be discussed in Chap. 5 and illustrated with ARMD data in Chap. 6.