Abstract
Abstract In this chapter, the estimation of relevant analytical figures of merit is reviewed, from univariate to multivariate and multiway calibration: sensitivity, limit of detection, and other analytical parameters. After a brief discussion on data properties, models, and algorithms, different sensitivity expressions are presented, based on the concept of net analyte signal as a function of concentration, and those derived from uncertainty propagation, as applied to univariate, first-order, and multiway (higher-order) calibrations. Relevant algorithms for which figures of merit are detailed are those based on multilinear decomposition, multivariate curve resolution-alternating least-squares, and partial least-squares with residual multilinearization. Comparison is made of the values furnished by the discussed expressions in going from lower- to higher-order data.
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