Abstract
Evolving factor analysis (EFA) is a general method for the analysis of multivariate data having an intrinsic order. Examples are data produced by many hyphenated techniques, such as high-performance liquid chromatography with photodiode array detection (HPLC-DAD) and the study of complex equilibria by ultraviolet spectrometry as a function of pH. EFA relies on an intrinsic order of the data and relies on only a few assumptions, such as nonnegativity of concentrations and the validity of Beer's law. The method can be applied to curve resolution and the assessment of peak purity in different disciplines of analytical chemistry. A didactic example from HPLC-DAD is used to illustrate the method. Possible limitations of EFA are also discussed.
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