Chapter 7: General Linear Model

In this chapter we discuss the ‘general’ case of the linear model, (y, X β, σ²V), where V is not necessarily the identity matrix. In contrast to the homoscedastic model, this general choice for V allows the observations to be correlated as well as to have different variances. Although we allowed X to be rank deficient in the preceding chapters, here for the first time, we also allow the dispersion matrix V to be rank-deficient i.e. singular. We refer to the linear model with a singular dispersion matrix as the singular linear model…