Theory of net analyte signal vectors in inverse regression

By Rasmus Bro, C. Andersen. 2003

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A closed‐form expression for computing the sensitivity in second‐order bilinear calibration (2005, background): “Notice that when unexpected components are absent, bn1⁄4bn,cal, making Equation (35) analogous to the definition of net analyte signal in first-order multivariate calibration models [46,47] However, Equations (34 and 35) provide the correct picture by modifying the regression coefficients due to the”
Partial Least Squares (2005, methodology): “Project the score ta: xa ¼ xa 1 tapa The output of PLS after a steps is ŷ ¼ yþ Pa j¼1 qjtj, which can equivalently be written as ŷ ¼ yþ ra ðx xÞ As derived in References [6,24], this version of PLS is defined in a population setting with an infinite amount of data points so that expectations are o”
Numerical construction of Green's functions in high dimensional elliptic problems with variable coefficients and analysis of renewable energy data via sparse and separable approximations (2012, background): “The analysis also depends on the notion of a net analyte signal (NAS) vector of the response, y, which is commonly defined as the component of the analyte profile that is orthogonal to the background profiles [24, 94],”
Sorting variables by using informative vectors as a strategy for feature selection in multivariate regression (2009, methodology): “[37], the NAS vector can be calculated using the following equation”