A set of hybrid least squares multivariate spectral analysis methods in
which spectral shapes of components or effects not present in the original
calibration step are added in a following prediction or calibration step
to improve the accuracy of the estimation of the amount of the original
components in the sampled mixture. The hybrid method herein means a
combination of an initial calibration step with subsequent analysis by an
inverse multivariate analysis method. A spectral shape herein means
normally the spectral shape of a non-calibrated chemical component in the
sample mixture but can also mean the spectral shapes of other sources of
spectral variation, including temperature drift, shifts between
spectrometers, spectrometer drift, etc. The shape can be continuous,
discontinuous, or even discrete points illustrative of the particular
effect.
