Outliers in partial least squares regression

The results shown are obtained by only modelling the alcoholic grade of the wines but the proposed solution is methodological and can be extended to calibrate any other parameter. The main conclusion is that on the studied data set, the samples declared abnormal (outliers) in the calibration step are not detected by only using the spectral (dis)similarity. However, the analysis of spectra shows the presence of a set of wines, not related with the outliers detected by PLS, whose presence in the calibration set is necessary to guarantee that the PLSR model built can be applied to future samples.