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This review covers the area of multivariate calibration; from pre-processing of data prior to modeling and applications of regression methods for calibration and prediction. The importance of pre-treatment of data is highlighted with many of the recently developed methods together with traditional methods. Several articles provide comparisons between different pre-processing methods. Methods for data from coupled chromatographic methods, which have found increasing use and where data pre-processing is a prerequisite for multivariate modeling, are also included. Many of the novel chemometric methods deal with model complexity and interpretation. A diverse set of applications are also presented and references are also given to early papers, making it possible to acquire a deeper knowledge of methods of interest.
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Gabrielsson et al. (2006) studied this question.
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