An algorithm for robust multiblock partial least squares predictive modelling
Abstract
A new algorithm for robust multiblock (data fusion) modelling in the presence of outlying observations is presented. The method a combination technique called iterative reweighted partial least squares and block order scale-independent component-wise modelling. based on automatic down-weighting such that their contribution minimal during estimation block-wise models, thus leading to minimally affected by outliers. test methods data sets (simulated real) observation are demonstrated.