MVC1: Software for Multivariate Calibration
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64144-2_12
Reference12 articles.
1. Allegrini, F., Fernández Pierna, J.A., Fragoso, W.D., Olivieri, A.C., Baeten, V., Dardenne, P.: Regression models based on new local strategies for near infrared spectroscopic data. Anal. Chim. Acta 933, 50–58 (2016)
2. Allegrini, F., Olivieri, A.C.: Linear or non-linear multivariate calibration models? That is the question. Anal. Chim. Acta 1226, 340248 (2022)
3. Antonelli, T.M., Olivieri, A.C.: Developing and implementing an R Shiny application to introduce multivariate calibration to advanced undergraduate students. J. Chem. Educ. 97, 1176–1180 (2020)
4. Arancibia, J.A., Martínez Delfa, G., Boschetti, C.E., Escandar, G.M., Olivieri, A.C.: Application of partial least-squares spectrophotometric multivariate calibration to the determination of 2-sec-butyl-4,6-dinitrophenol (dinoseb) and 2,6-dinitro-p-cresol in industrial and water samples containing hydrocarbons. Anal. Chim. Acta 553, 141–147 (2005)
5. Boschetti, C.E., Olivieri, A.C.: A new genetic algorithm applied to the near-infrared analysis of gasolines. J. NIR Spectrosc. 12, 85–91 (2004)
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