The article is structured as follows. Methodology section presents the Generalized Least Squares (GLS) approach for functional regression models. The estimation of the different parameters (for the regression function or the dependence) is usually done using maximum likelihood although, as an alternative, we introduce an iterative GLS (iGLS) procedure that provides similar results. The latter could be interesting when the structure of the dependence is complicated. The practical performances of the GLS and iGLS procedures are compared, by means of a simulation study. Real example section applies these models to the prediction of the influenza rate in a region of Spain.