(1) Département d’épidémiologie animale, Les Croix, AFSSA, BP53, 22440 Ploufragan, France;(2) ENITIAA-INRA, Unité de Sensométrie et Chimiométrie, Rue de la Géraudière, BP 82225, 44322 Nantes Cedex, France
Abstract:
Several papers have already stressed the interest of latent root regression and its similarities to partial least squares
regression. A new formulation of this method which makes it even simpler than the original method to set up a prediction model
is discussed. Furthermore, it is shown how this method can be extended not only to the case where it is desired to predict
several response variables from a set of predictors but also to the multiblock setting where the aim is to predict one or
several data sets from several other data sets. The interest of the method is illustrated on the basis of a data set pertaining
to epidemiology.