Abstract

Two data-handling techniques, least-squares fitting and cross-correlation, have been used for three-component analysis under comparable conditions with the use of both simulated and real data. Factors considered are the effect of variation in degree of peak overlap, signal-to-noise ratio, the effect of peak width variations when peak maxima occur at the same position, and the effect of varying peak intensities. A series of lipid mixtures was analyzed by each method with the use of infrared absorption. This permits comparison of these results with earlier reports. Both least-squares and cross-correlation can be used with samples that are outside the applicable range of the earlier work. In this comparison, the least-squares results are somewhat better than those from cross-correlation.

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