Generalized linear model based on latent factors and supervised components
Author:
Funder
Agence Nationale de la Recherche
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00180-024-01544-8.pdf
Reference48 articles.
1. Bartholomew DJ, Knott M, Moustaki I (2011) Latent variable models and factor analysis: a unified approach, 3rd edn. John Wiley & Sons, New Jersey
2. Bry X, Verron T (2015) THEME: THEmatic model exploration through multiple co-structure maximization. J Chemom 29:637–647. https://doi.org/10.1002/cem.2759
3. Bry X, Trottier C, Verron T et al (2013) Supervised component generalized linear regression using a PLS-extension of the Fisher scoring algorithm. J Multivar Anal 119:47–6. https://doi.org/10.1016/j.jmva.2013.03.013
4. Bry X, Simac T, El Ghachi SE et al (2020) Bridging data exploration and modeling in event-history analysis: the supervised-component Cox regression. Math Popul Stud 27(3):139–174. https://doi.org/10.1080/08898480.2018.1553413
5. Bry X, Trottier C, Mortier F et al (2020) Component-based regularization of a multivariate GLM with a thematic partitioning of the explanatory variables. Stat Model 20(1):96–111. https://doi.org/10.1177/1471082X18810114
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