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A simple approach to uncertainty propagation in preprocessed multivariate calibration
Author(s) -
Olivieri Alejandro C.
Publication year - 2002
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.716
Subject(s) - monte carlo method , calibration , multivariate statistics , propagation of uncertainty , binary number , preprocessor , noise (video) , algorithm , computer science , statistics , statistical physics , mathematics , artificial intelligence , physics , arithmetic , image (mathematics)
A simple approach is described to estimate the confidence limit for the concentrations predicted by multivariate calibration when preprocessing techniques such as orthogonal signal correction or net analyte calculation are applied. It involves reconstructing the unpreprocessed data using the extracted spectral factors and those employed for prediction in order to correctly estimate the sample leverages. Monte Carlo simulations carried out by adding random noise to both concentrations and analytical signals for theoretical binary mixtures are in excellent agreement with the calculations. Experimental multicomponent examples were studied by a similar Monte Carlo approach, and the obtained variances are also in agreement with the calculated values. Implications concerning the limits of detection in the latter cases are also discussed. Copyright © 2002 John Wiley & Sons, Ltd.