Abstract
Multivariate calibration models are usually implemented by first selecting appropriate calibration samples and working wavelengths. Different procedures are discussed for performing these important activities.
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References
Brown, C.D., Green, R.L.: Critical factors limiting the interpretation of regression vectors in multivariate calibration. Trends Anal. Chem. 28, 506–514 (2009)
Centner, V., Massart, D.L., de Noord, O.E., de Jong, S., Vandeginste, B.M., Sterna, C.: Elimination of uninformative variables for multivariate calibration. Anal. Chem. 68, 3851–3858 (1996)
Galvao, R.K.H., Araujo, M.C.U., Jose, G.E., Pontes, M.J.C., Silva, E.C., Saldanha, T.C.B.: A method for calibration and validation subset partitioning. Talanta. 67, 736–740 (2005)
Kalivas, J.H., Roberts, N., Sutter, J.M.: Global optimization by simulated annealing with wavelength selection for ultraviolet–visible spectrophotometry. Anal. Chem. 61, 2024–2030 (1989)
Kennard, W., Stone, L.A.: Computer aided design of experiments. Technometrics. 11, 137–148 (1969)
Leardi, R., Lupiáñez González, A.: Genetic algorithms applied to feature selection in PLS regression: how and when to use them. Chemom. Intell. Lab. Syst. 41, 195–207 (1998)
Mehmood, T., Liland, K.H., Snipen, L., Sæbø, S.: A review of variable selection methods in partial least squares regression. Chemom. Intell. Lab. Syst. 118, 62–69 (2012)
Nørgaard, L., Saudland, A., Wagner, J., Nielsen, J.P., Munck, L., Engelsen, S.B.: Interval partial least-squares regression (iPLS): a comparative chemometric study with an example from near-infrared spectroscopy. Appl. Spectrosc. 54, 413–419 (2000)
Shamsipur, M., Zare-Shahabadi, V., Hemmateenejad, B., Akhond, M.: Ant colony optimisation: a powerful tool for wavelength selection. J. Chemom. 20, 146–157 (2006)
Sorol, N., Arancibia, E., Bortolato, S.A., Olivieri, A.C.: Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice. A test field for variable selection methods. Chemom. Intell. Lab. Syst. 102, 100–109 (2010)
Thomas, E.V., Haaland, D.M.: Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information. Anal. Chem. 60, 1193–1202 (1988)
Xu, L., Jiang, J.H., Wu, H.L., Shen, G.L., Yu, R.Q.: Variable-weighted PLS. Chemom. Intell. Lab. Syst. 85, 140–143 (2007)
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Olivieri, A.C. (2018). Sample and Sensor Selection. In: Introduction to Multivariate Calibration. Springer, Cham. https://doi.org/10.1007/978-3-319-97097-4_8
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DOI: https://doi.org/10.1007/978-3-319-97097-4_8
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