EVOLVING PROJECTION ANALYSIS OF MULTICOMPONENT MIXTURES

The application of evolving projection analysis (EPA) to second-order bilinear data sets consisting of more than two components is described . EPA is a method for rank analysis of ordered data matrices where the components appear sequentially as a function of time or some other or dinal variable. It was found that extension of the method to mixtures of more than two components was best accomplished using principal comp onents analysis to preprocess the data. The algorithm is demonstrated using simulated four-component chromatographic data, and experimental data from liquid chromatography (three- and four-component mixtures) a nd a spectrophotometric titration (four components), both employing UV -visible diode array detection.