Uncommon multivariate statistical methods for environmental studies: A review
In this paper we describe the characteristics and the applications of the multivariate methods for spectroscopic and chromatographic techniques independent component analysis (ICA) and two-dimensional correlation spectroscopy (2DCOS) focused to their use in environmental studies. In our opinion, the...
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_22141588_v6-7_n_p31_Mecozzi |
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todo:paper_22141588_v6-7_n_p31_Mecozzi2023-10-03T16:40:37Z Uncommon multivariate statistical methods for environmental studies: A review Mecozzi, M. Tudino, M.B. Finoia, M.G. Conti, M.E. Chromatographic analysis Environmental studies Independent component analysis Multivariate methods Spectroscopic analysis Two-dimensional correlation spectroscopy In this paper we describe the characteristics and the applications of the multivariate methods for spectroscopic and chromatographic techniques independent component analysis (ICA) and two-dimensional correlation spectroscopy (2DCOS) focused to their use in environmental studies. In our opinion, these methods are important because they allow to characterize environmental samples with different aims and scopes from those generally obtained by means of more common multivariate methods such as principal component analysis (PCA) and partial least squares (PLS). The new insights of these methods in recent environmental studies are reviewed and debated. © 2015 Elsevier B.V. Fil:Tudino, M.B. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_22141588_v6-7_n_p31_Mecozzi |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Chromatographic analysis Environmental studies Independent component analysis Multivariate methods Spectroscopic analysis Two-dimensional correlation spectroscopy |
| spellingShingle |
Chromatographic analysis Environmental studies Independent component analysis Multivariate methods Spectroscopic analysis Two-dimensional correlation spectroscopy Mecozzi, M. Tudino, M.B. Finoia, M.G. Conti, M.E. Uncommon multivariate statistical methods for environmental studies: A review |
| topic_facet |
Chromatographic analysis Environmental studies Independent component analysis Multivariate methods Spectroscopic analysis Two-dimensional correlation spectroscopy |
| description |
In this paper we describe the characteristics and the applications of the multivariate methods for spectroscopic and chromatographic techniques independent component analysis (ICA) and two-dimensional correlation spectroscopy (2DCOS) focused to their use in environmental studies. In our opinion, these methods are important because they allow to characterize environmental samples with different aims and scopes from those generally obtained by means of more common multivariate methods such as principal component analysis (PCA) and partial least squares (PLS). The new insights of these methods in recent environmental studies are reviewed and debated. © 2015 Elsevier B.V. |
| format |
JOUR |
| author |
Mecozzi, M. Tudino, M.B. Finoia, M.G. Conti, M.E. |
| author_facet |
Mecozzi, M. Tudino, M.B. Finoia, M.G. Conti, M.E. |
| author_sort |
Mecozzi, M. |
| title |
Uncommon multivariate statistical methods for environmental studies: A review |
| title_short |
Uncommon multivariate statistical methods for environmental studies: A review |
| title_full |
Uncommon multivariate statistical methods for environmental studies: A review |
| title_fullStr |
Uncommon multivariate statistical methods for environmental studies: A review |
| title_full_unstemmed |
Uncommon multivariate statistical methods for environmental studies: A review |
| title_sort |
uncommon multivariate statistical methods for environmental studies: a review |
| url |
http://hdl.handle.net/20.500.12110/paper_22141588_v6-7_n_p31_Mecozzi |
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