DIRECT DISTANCE MEASURES IN FACTOR-ANALYSIS SPECTRAL RESOLUTION

A factor analysis algorithm that estimates the spectra of mixture components using the set of most dissimilar rows and/or columns is described and illustrated. This algorithm uses the distance as a measure of spectral similarity and is suitable for application to a variety of the bilinear matrix-formatted data types produced by hyphenated and multidimensional analytical techniques. The algorithm requires that the data matrix contain at least one row or column that corresponds to the pure spectrum of each component to effect accurate spectral resolution. The performance of the method is illustrated using the resolution of excitation and emission spectra of up to four components from experimental fluorescence excitation-emission matrices (EEMs). In the case of the EEM, characteristic bands in an emission spectrum effect resolution of the excitation spectrum of the corresponding component, while characteristic bands in an excitation spectrum lead to resolution of the corresponding emission spectrum. The use of the set of most dissimilar rows and columns to evaluate the degree of overlap in the component spectra and compare the quality of row and column solutions is also described.