GAMBoost: Generalized linear and additive models by likelihood based boosting. This package provides routines for fitting generalized linear and and generalized additive models by likelihood based boosting, using penalized B-splines
Keywords for this software
References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- De Bin, Riccardo: Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages \itCoxBoost and \itmboost (2016)
- Porzelius, Christine; Johannes, Marc; Binder, Harald; Beißbarth, Tim: Supporting information leveraging external knowledge on molecular interactions in classification methods for risk prediction of patients (2011)
- Kriegler, Brian; Berk, Richard: Small area estimation of the homeless in Los Angeles: an application of cost-sensitive stochastic gradient boosting (2010)
- Bühlmann, Peter; Hothorn, Torsten: Boosting algorithms: regularization, prediction and model fitting (2007)