The multivariate calibration problem is a problem of predicting the concentration in an unknown sample, cun, from the response vector of an unknown sample, run (J responses). The predicting equation can be arranged in the form ĉun = runTR+c. (1) R+ is the pseudo-inverse of the calibration set matrix of responses, R, whose column indices correspond to the J sensors or wavelengths and row indices correspond to the I samples (individuals), and c is the vector of concentrations for the I samples of the analyte in each of the calibration samples. Derivation of Eq. 1 is described in Ref. 1. The PLS regression involves solution of the predicting equation.
Avraham Lorber and Bruce R. Kowalski, "A Note on the Use of the Partial Least-Squares Method for Multivariate Calibration," Appl. Spectrosc. 42, 1572-1574 (1988)
References are not available for this paper.
OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.