The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Variable selection in regression—a tutorial
Abstract
This paper provides a practical guide to variable selection in chemometrics with a focus on regression‐based calibration models. Several approaches, such as genetic algorithms (GAs), jack‐knifing, forward selection, etc., are explained; it is also explained how to choose between different kinds of variable selection methods. The emphasis in this paper is on how to use variable selection in practice and avoid the most common pitfalls. Copyright © 2010 John Wiley & Sons, Ltd.
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Cites
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Regression Shrinkage and Selection via The Lasso: A Retrospective
Tibshirani, R. (2011) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2011.00771.x · Cited by 3,589
Babyak, M. A. (2004) · Psychosomatic Medicine · doi:10.1097/01.psy.0000127692.23278.a9 · Cited by 2,061
Performance of some variable selection methods when multicollinearity is present
Chong, I.-G., & Jun, C.-H. (2005) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2004.12.011 · Cited by 2,049
Nørgaard, L., Saudland, A., Wagner, J., Nielsen, J. P., Munck, L., & Engelsen, S. B. (2000) · Applied Spectroscopy · doi:10.1366/0003702001949500 · Cited by 1,361
3D QSAR in drug design : theory, methods and applications
Kubinyi, H. (2000) · Medical Entomology and Zoology · Cited by 858
Genetic algorithms as a strategy for feature selection
Leardi, R., Boggia, R., & Terrile, M. (1992) · Journal of Chemometrics · doi:10.1002/cem.1180060506 · Cited by 828
Martens, H., & Martens, M. (2000) · Food Quality and Preference · doi:10.1016/s0950-3293(99)00039-7 · Cited by 722
Osborne, M. R., Presnell, B., & Turlach, B. A. (2000) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2000.10474883 · Cited by 696
Wehrens, R., Putter, H., & Buydens, L. M. C. (2000) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(00)00102-7 · Cited by 490
Cited by
Gorrochategui, E., Jaumot, J., Lacorte, S., & Tauler, R. (2016) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2016.07.004 · Cited by 352
Bigdeli, A., Palchetti, S., Pozzi, D., Hormozi-Nezhad, M. R., Baldelli Bombelli, F., Caracciolo, G., & Mahmoudi, M. (2016) · ACS Nano · doi:10.1021/acsnano.6b00261 · Cited by 157
Rolinger, L., Rüdt, M., & Hubbuch, J. (2020) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-020-02407-z · Cited by 126
Feidl, F., Garbellini, S., Vogg, S., Sokolov, M., Souquet, J., Broly, H., Butté, A., & Morbidelli, M. (2019) · Biotechnology Progress · doi:10.1002/btpr.2847 · Cited by 59
Rolinger, L., Rüdt, M., & Hubbuch, J. (2021) · Biotechnology and Bioengineering · doi:10.1002/bit.27894 · Cited by 33
Metadata
- Authors
- Andersen, C. M., & Bro, R.
- Venue
- Journal of Chemometrics
- Publisher
- Wiley
- Published
- 2010-11
- Volume
- 24
- Issue
- 11-12
- Pages
- 728-737
- ISSN
- 0886-9383 (ISSN-L)
- 1099-128X
- OpenAlex
- W2037226761
- Cited by
- 697
- References
- 21
- FWCI
- 23.49
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
