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Use of the Kalman filter for multivariate calibration in a real system and its comparison with CLS and pure component calibration methods
Author(s) -
Péarezarribas L. V.,
NavarroVilloslada F.,
LeónGonzalez M. E.,
PoloDíez L. M.
Publication year - 1993
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.1180070405
Subject(s) - calibration , kalman filter , standard deviation , multivariate statistics , mathematics , ternary operation , extended kalman filter , binary number , component (thermodynamics) , partial least squares regression , statistics , computer science , thermodynamics , physics , arithmetic , programming language
The usefulness of the Kalman filter as an algorithm for calibration in a real system is shown. Results are compared with classical least squares and pure component calibration. The prediction of four priority pollutant chlorophenols in binary, ternary and quaternary mixtures was also carried out by Kalman filtering. The condition number, standard deviation and prediction error have been employed to choose the most suitable wavelength range. Comparison of the standard error of prediction in the validation set shows significant differences between the evaluated chlorophenols, the best results being obtained with Kalman multivariate calibration.