Strategies for direct versus inverse modeling methods

2 Strategies for direct versus inverse modeling methods 

In Section 12.3.2, the fundamental differences between direct and inverse modeling methods were discussed. As will be discussed here, this distinction is not just a convenient means for classifying quantitative regression methods, but has profound implications regarding calibration strategy and supporting infrastructure. 

Extended-CLS (ELS)-type modeling, can be supported with the same calibration strategies as those mentioned above for direct methods, with an additional consideration one must also collect data that can be used to estimate unknown contributions to the spectrum. Such characterization of the unknown contributors often requires the collection of sufficiently relevant process data, or at least reasonable a priori estimates of expected interference effects, such as baseline effects and water vapor interferences, in the process spectra. 

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