INVESTIGADORES
GOICOECHEA Hector Casimiro
artículos
Título:
MVC1: An integrated MATLAB toolbox for first-order multivariate calibration
Autor/es:
A.C. OLIVIERI, H.C. GOICOECHEA AND F. IÑÓN.
Revista:
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
Editorial:
Elsevier
Referencias:
Lugar: Amsterdam; Año: 2004 p. 189 - 197
ISSN:
0169-7439
Resumen:
Multivariate calibration 1 (MVC1), a MatLab® toolbox for implementing up to twelve different first-order calibration methodologies through easily managed graphical user interfaces, is presented. The toolbox accepts different input data formats (either arranged as matrices or vectors contained in raw data files or in already existing MatLab variables), and incorporates many pre-processing algorithms in order to improve prediction capabilities. The development and validation of each model and its subsequent application to unknown samples is straightforward. Prediction results are produced along analytical figures of merit and standard errors calculated by uncertainty propagation. Moreover, the toolbox allows one to manually select working sensor regions or to automatically find which region provides the minimum error. It also generates many different plots regarding model performance, including outliers detection, facilitating both model evaluation and interpretation.
