BUCHI NIRCal - Manual (Page 54)

NIRCal 5.5 Software Manual
54 NIRCal 5.5 Manual, Version A
3.1.6 Principal Component Regression: PCR
Principal Component Analysis (PCA) with subsequent MLR is called Principal Component Regression
(PCR). As a first step, the principal components and scores are calculated with PCA. The second step
is a multiple linear regression MLR using the scores and property values (concentrations).
Since the calculation of the principal components is performed with the spectral data
– independently
of the subsequent regression calculation for the correlation of the quantitative values – any number of
parameters can be simultaneously included in a PCR calibration. This also means that the relevant
PCs for the determination of the property are not necessarily the ones describing the biggest spectral
variations.
3.1.7 Partial Least Squares Regression: PLS
Partial Least Squares Regression (PLS) calculates the PC's with iteration in several steps, with
spectral information and property values being taken into account simultaneously.
This calculation method is more up to date than the PCR. Based on the principle of recursion, PC's
and scores are also calculated as with PCR, but the quantitative reference values are included in the
calculation from the beginning.
Each of the calculated PC's in the PLS procedure contains information about the original property
values (true concentration) of the samples, with the first PCs (unlike PCR) always showing the highest
correlation.