R package gamsel: Fit Regularization Path for Generalized Additive Models. Using overlap grouped lasso penalties, gamsel selects whether a term in a gam is nonzero, linear, or a non-linear spline (up to a specified max df per variable). It fits the entire regularization path on a grid of values for the overall penalty lambda, both for gaussian and binomial families.

References in zbMATH (referenced in 22 articles )

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  1. Gambella, Claudio; Ghaddar, Bissan; Naoum-Sawaya, Joe: Optimization problems for machine learning: a survey (2021)
  2. Helwig, Nathaniel E.: Spectrally sparse nonparametric regression via elastic net regularized smoothers (2021)
  3. Fan, Yingying; Demirkaya, Emre; Li, Gaorong; Lv, Jinchi: RANK: large-scale inference with graphical nonlinear knockoffs (2020)
  4. Meulman, Jacqueline J.; van der Kooij, Anita J.; Duisters, Kevin L. W.: ROS regression: integrating regularization with optimal scaling regression (2019)
  5. Boyd, Nicholas; Hastie, Trevor; Boyd, Stephen; Recht, Benjamin; Jordan, Michael I.: Saturating splines and feature selection (2018)
  6. Liang, Faming; Li, Qizhai; Zhou, Lei: Bayesian neural networks for selection of drug sensitive genes (2018)
  7. Vatter, Thibault; Nagler, Thomas: Generalized additive models for pair-copula constructions (2018)
  8. Nummi, Tapio; Möttönen, Jyrki; Tuomisto, Martti T.: Testing of multivariate spline growth model (2017)
  9. Yan, Xiaohan; Bien, Jacob: Hierarchical sparse modeling: a choice of two group Lasso formulations (2017)
  10. Kauermann, Göran; Westerheide, Nina: To move or not to move to find a new job: spatial duration time model with dynamic covariate effects (2012)
  11. Yanagihara, Hirokazu: A non-iterative optimization method for smoothness in penalized spline regression (2012)
  12. Nummi, Tapio; Pan, Jianxin; Siren, Tarja; Liu, Kun: Testing for cubic smoothing splines under dependent data (2011)
  13. Wand, M. P.; Ormerod, J. T.: Penalized wavelets: embedding wavelets into semiparametric regression (2011)
  14. Cressie, Noel; Johannesson, Gardar: Fixed rank Kriging for very large spatial data sets (2008)
  15. Ormerod, John T.; Wand, M. P.; Koch, Inge: Penalized spline support vector classifiers computational issues (2008)
  16. Kauermann, Göran: Nonparametric models and their estimation (2006)
  17. Wand, M. P.: Smoothing and mixed models (2003)
  18. Aerts, M.; Claeskens, G.; Wand, M. P.: Some theory for penalized spline generalized additive models (2002)
  19. Cantoni, Eva; Hastie, Trevor: Degrees-of-freedom tests for smoothing splines (2002)
  20. Coull, Brent A.; Ruppert, David; Wand, M. P.: Simple incorporation of interactions into additive models (2001)

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