Literature DB >> 17420021

Multivariate calibration.

M Forina1, S Lanteri, M Casale.   

Abstract

The bases of multivariate calibration are presented with special attention to some points usually not considered or underevaluated, i.e., the sampling design, the number of samples necessary to obtain a reliable regression model, the effect of noisy predictors, the significance of the parameters used to evaluate the performance ability of the regression model.

Mesh:

Year:  2007        PMID: 17420021     DOI: 10.1016/j.chroma.2007.03.082

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  1 in total

1.  Reduction of the Number of Samples for Cost-Effective Hyperspectral Grape Quality Predictive Models.

Authors:  Julio Nogales-Bueno; Francisco José Rodríguez-Pulido; Berta Baca-Bocanegra; Dolores Pérez-Marin; Francisco José Heredia; Ana Garrido-Varo; José Miguel Hernández-Hierro
Journal:  Foods       Date:  2021-01-23
  1 in total

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