Investigation of window factor analysis and matrix regression analysis in chromatography

Abstract Window factor analysis (WFA), a self-modeling chemometric method for obtaining the concentration profiles of individual components from evolutionary processes, is applied to unresolved liquid chromatograms. WFA makes use of the fact that each component lies in a specific region along the evolutionary axis, called the ‘window’. The high-performance liquid chromatograms of various mixtures of toluene, ethylbenzene, m -xylene and naphthalene, in methanol solvent, were recorded with an ultraviolet diode-array detector. Although the quantitative results obtained by WFA did not agree exactly with the known concentrations, the results were in agreement with those obtained by rank annihilation factor analysis and matrix regression analysis. Derivation of matrix regression analysis, developed during this investigation, is presented.