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Vol. 28 No. 3
May-June 2006

Making an imPACt | Recent IUPAC technical reports and recommendations that affect the many fields of pure and applied chemistry.
See also www.iupac.org/publications/pac

Uncertainty Estimation and Figures of Merit for Multivariate Calibration (IUPAC Technical Report)

Alejandro C. Olivieri, Nicolaas (Klaas) M. Faber, Joan Ferré, Ricard Boqué, John H. Kalivas, and Howard Mark
Pure and Applied Chemistry
Vol. 78, No. 3, pp. 633-661 (2006)
doi:10.1351/pac200678030633

This report 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 reliable only 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 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.

Illustration of how a univariate model will lead to severely biased predictions when unsuspected interferences give a variable contribution to the signal, whereas multiple measurements may permit accurate prediction in such a situation.

 

www.iupac.org/publications/pac/2006/7803/7803x0633.html


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