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In This Section
Volume 78, Issue 3 (Jan 2006)


Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report)

Alejandro C. Olivieri
  • Corresponding author
  • Departamento de Química Analítica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, Rosario S2002LRK, Argentina
/ Nicolaas M. Faber
  • Corresponding author
  • Chemometry Consultancy, Rubensstraat 7, 6717 VD Ede, The Netherlands
/ Joan Ferré
  • Corresponding author
  • Department of Analytical and Organic Chemistry, Rovira i Virgili University, 43007 Tarragona, Spain
/ Ricard Boqué
  • Corresponding author
  • Department of Analytical and Organic Chemistry, Rovira i Virgili University, 43007 Tarragona, Spain
/ John H. Kalivas
  • Corresponding author
  • Department of Chemistry, Idaho State University, Pocatello, ID 83209, USA
/ Howard Mark
  • Corresponding author
  • Mark Electronics, 69 Jamie Court, Suffern, NY 10901, USA
Published Online: 2009-01-01 | DOI: https://doi.org/10.1351/pac200678030633

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.

Keywords: chemometrics; figures of merit; IUPAC Analytical Chemistry Division; limit of detection; multivariate calibration; prediction interval; results reporting; standard error of prediction

Project Year: 2004, Project Code: 2004-041-1-500

About the article

Published Online: 2009-01-01

Published in Print: 2006-01-01

Citation Information: Pure and Applied Chemistry, ISSN (Online) 1365-3075, ISSN (Print) 0033-4545, DOI: https://doi.org/10.1351/pac200678030633. Export Citation

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