Core argument of the Ph.D. Thesis is Partial Least Squares (PLS), a class of techniques for modelling relations between sets of observed quantities through latent variables in presence of collinearity. Aim of the thesis is to describe PLS, starting from an overview of the discipline where PLS takes place up to the application of PLS to a real dataset, moving through a critical comparison with alternative techniques. Conclusions are made and future perspectives are highlighted.
