Pure and Applied Chemistry
The Scientific Journal of IUPAC
Ed. by Burrows, Hugh / Weir, Ron / Stohner, Jürgen
12 Issues per year
IMPACT FACTOR 2016: 2.626
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CiteScore 2016: 2.45
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Source Normalized Impact per Paper (SNIP) 2016: 1.049
Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report)
This paper gives an introduction to multivariate calibration from a chemometrics perspective and reviews the various proposals to generalize the well-established univariate methodology to the multivariate domain. Univariate calibration leads to relatively simple models with a sound statistical underpinning. The associated uncertainty estimation and figures of merit are thoroughly covered in several official documents. However, univariate model predictions for unknown samples are only reliable if the signal is sufficiently selective for the analyte of interest. By contrast, multivariate calibration methods may produce valid predictions also from highly unselective data. A case in point is quantification from near-infrared (NIR) spectra. With the ever-increasing sophistication of analytical instruments inevitably comes a suite of multivariate calibration methods, each with its own underlying assumptions and statistical properties. As a result, uncertainty estimation and figures of merit for multivariate calibration methods has become a subject of active research, especially in the field of chemometrics.
Project Year: 2004, Project Code: 2004-041-1-500
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