Patent ID: 6687620
Filing Date: 2004-02-03
Classification: G01N

Abstract:
A method for analyzing multivariate spectral data, comprising the steps of:a) creating a calibration model for a calibration set of multivariate spectral data A by: i) obtaining a set of reference component values C representative of at least one of the spectrally active components in the calibration set of multivariate spectral data A, ii) estimating pure-component spectra {circumflex over (K)} for the at least one of the spectrally active components according to {circumflex over (K)}=(CTC)âˆ’1CTA=C+A, iii) obtaining spectral residuals EA according to EA=Aâˆ’C{circumflex over (K)}, and iv) augmenting the estimated pure-component spectra {circumflex over (K)} with at least one vector of the spectral residuals EA to obtain augmented pure-component spectra {tilde over ({circumflex over (K)})}; and b) predicting a set of component values {tilde over ({circumflex over (C)})} for a prediction set of multivariate spectral data AP by: i) further augmenting the augmented pure-component spectra {tilde over ({circumflex over (K)})} with at least one vector representing a spectral shape that is representative of at least one additional source of spectral variation in the prediction set, and ii) predicting the set of component values {tilde over ({circumflex over (C)})} using the further augmented pure-component spectra {tilde over ({circumflex over (K)})} according to {tilde over ({circumflex over (C)})}=AP{tilde over ({circumflex over (K)})}T({tilde over ({circumflex over (K)})}{tilde over ({circumflex over (K)})}T)âˆ’1=AP({tilde over ({circumflex over (K)})}T)+.