The multivariate calibration problem in chemistry solved by the PLS method
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There are many supervised methods, with partial least-squares discriminant analysis (PLS-DA) or its variants being the most commonly used for comparing two groups.
“There are a large number of supervised methods (120, 127), with the most commonly used analysis for comparing 2 groups being partial least-squares discriminant analysis (PLS-DA) (132) or one of its several variants.”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [132]
Cites
Draper, N. R., & Smith, H. (2005) · Technometrics · doi:10.1198/tech.2005.s303 · Cited by 17,993 · see citing works
Cross validatory choice and assessment of statistical predictions
Stone, M. (1974) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1974.tb00994.x · Cited by 10,881 · see citing works
Hahn, G. J., Draper, N. R., & Smith, H. C. (1982) · Technometrics · doi:10.2307/1267833 · Cited by 5,820 · see citing works
Wold, S., Ruhe, A., Wold, H., & Dunn, III (1984) · SIAM Journal on Scientific and Statistical Computing · doi:10.1137/0905052 · Cited by 2,529 · see citing works
Self-citationCross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
Wold, S. (1978) · Technometrics · doi:10.1080/00401706.1978.10489693 · Cited by 2,506 · see citing works
Self-citationGeneralized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
Marquardt, D. W. (1970) · Technometrics · doi:10.2307/1267205 · Cited by 2,284 · see citing works
Pattern recognition by means of disjoint principal components models
Wold, S. (1976) · Pattern Recognition · doi:10.1016/0031-3203(76)90014-5 · Cited by 1,166 · see citing works
Self-citation(1960) · The Computer Journal · doi:10.1093/comjnl/3.2.75 · Cited by 927 · see citing works
(1982) · Cited by 842 · see citing works
Practical Approximate Solutions to Linear Operator Equations When the Data are Noisy
Wahba, G. (1977) · SIAM Journal on Numerical Analysis · doi:10.1137/0714044 · Cited by 799 · see citing works
SIMCA: A Method for Analyzing Chemical Data in Terms of Similarity and Analogy
Wold, S., & Sjöstróm, M. (1977) · ACS symposium series · doi:10.1021/bk-1977-0052.ch012 · Cited by 598 · see citing works
Self-citationChemometrics: Views and Propositions
Kowalski, B. R. (1975) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci60004a002 · Cited by 79 · see citing works
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Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2004.03.005 · Cited by 6,312 · see citing works
The food metabolome: a window over dietary exposure
Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.076133 · Cited by 519 · see citing works
Martens, H., & Stark, E. (1991) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/0731-7085(91)80188-f · Cited by 515 · see citing works
Self-citationEditorial: Perspectives on Partial Least Squares
Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010) · Handbook of Partial Least Squares · doi:10.1007/978-3-540-32827-8_1 · Cited by 108 · see citing works
Garali, I., Adanyeguh, I. M., Ichou, F., Perlbarg, V., Seyer, A., Colsch, B., Moszer, I., Guillemot, V., Durr, A., Mochel, F., et al. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bbx060 · Cited by 68 · see citing works
- Authors
- Wold, S., Martens, H., & Wold, H.
- ORCID
- Martens, H.
- Venue
- Lecture notes in mathematics
- Publisher
- Springer Berlin Heidelberg
- Published
- 1983
- Pages
- 286-293
- ISSN
- 0075-8434 (ISSN-L)
- 1617-9692
- OpenAlex
- W3644042
- Cited by
- 1,185
- References
- 12
- Citations by year
- 2026: 23 · 2025: 31 · 2024: 40 · 2023: 60 · 2022: 56 · 2021: 98 · 2020: 65 · 2019: 60 · 2018: 61 · 2017: 50 · 2016: 50 · 2015: 48 · 2014: 58 · 2013: 68 · 2012: 38
- FWCI
- 19.55
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in mathematics (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Keywords
- multivariate calibration, partial least squares, matrix pencils, chemometrics, linear least squares
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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