Functional Analysis of Chemometric Data

Ana M. Aguilera; Manuel Escabias; Mariano J. Valderrama; M. Carmen Aguilera-Morillo

doi:10.4236/ojs.2013.35039

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Open Journal of Statistics > Vol.3 No.5, October 2013

Functional Analysis of Chemometric Data ()

Ana M. Aguilera, Manuel Escabias, Mariano J. Valderrama, M. Carmen Aguilera-Morillo

Department of Statistics, University of Granada, Granada, Spain.

DOI: 10.4236/ojs.2013.35039 PDF HTML XML 4,346 Downloads 6,656 Views Citations

Abstract

The objective of this paper is to present a review of different calibration and classification methods for functional data in the context of chemometric applications. In chemometric, it is usual to measure certain parameters in terms of a set of spectrometric curves that are observed in a finite set of points (functional data). Although the predictor variable is clearly functional, this problem is usually solved by using multivariate calibration techniques that consider it as a finite set of variables associated with the observed points (wavelengths or times). But these explicative variables are highly correlated and it is therefore more informative to reconstruct first the true functional form of the predictor curves. Although it has been published in several articles related to the implementation of functional data analysis techniques in chemometric, their power to solve real problems is not yet well known. Because of this the extension of multivariate calibration techniques (linear regression, principal component regression and partial least squares) and classification methods (linear discriminant analysis and logistic regression) to the functional domain and some relevant chemometric applications are reviewed in this paper.

Keywords

Functional Data Analysis; B-Splines; Functional Principal Component Regression; Functional Partial Least Squares; Functional Logit Models; Functional Linear Discriminant Analysis; Spectroscopy; NIR Spectra

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A. Aguilera, M. Escabias, M. Valderrama and M. Aguilera-Morillo, "Functional Analysis of Chemometric Data," Open Journal of Statistics, Vol. 3 No. 5, 2013, pp. 334-343. doi: 10.4236/ojs.2013.35039.

Conflicts of Interest

The authors declare no conflicts of interest.

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