Package: mboost Title: Model-Based Boosting Version: 2.9-14 Authors@R: c(person("Torsten", "Hothorn", role = c("cre", "aut"), email = "Torsten.Hothorn@R-project.org", comment = c(ORCID = "0000-0001-8301-0471")), person("Peter", "Buehlmann", role = "aut", comment = c(ORCID = "0000-0002-1782-6015")), person("Thomas", "Kneib", role = "aut", comment = c(ORCID = "0000-0003-3390-0972")), person("Matthias", "Schmid", role = "aut", comment = c(ORCID = "0000-0002-0788-0317")), person("Benjamin", "Hofner", role = "aut", comment = c(ORCID = "0000-0003-2810-3186")), person("Fabian", "Otto-Sobotka", role = "ctb", comment = c(ORCID = "0000-0002-9874-1311")), person("Fabian", "Scheipl", role = "ctb", comment = c(ORCID = "0000-0001-8172-3603")), person("Andreas", "Mayr", role = "ctb", comment = c(ORCID = "0000-0001-7106-9732"))) Description: Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data. Models and algorithms are described in , a hands-on tutorial is available from . The package allows user-specified loss functions and base-learners. Depends: R (>= 3.2.0), methods, stats, parallel, stabs (>= 0.5-0) Imports: Matrix, survival (>= 3.2-10), splines, lattice, nnls, quadprog, utils, graphics, grDevices, partykit (>= 1.2-1) Suggests: TH.data, MASS, fields, BayesX, gbm, mlbench, RColorBrewer, rpart (>= 4.0-3), randomForest, nnet, kangar00, bibtex, lme4, nlme, cobs License: GPL-2 BugReports: https://github.com/boost-R/mboost/issues URL: https://github.com/boost-R/mboost Encoding: UTF-8 Repository: https://boost-r.r-universe.dev Date/Publication: 2026-09-22 10:27:50 UTC RemoteUrl: https://github.com/boost-r/mboost RemoteRef: HEAD RemoteSha: 967f942aa72cfeb38d129b88d97744932e5bb98e NeedsCompilation: yes Packaged: 2026-09-22 15:31:35 UTC; root Author: Torsten Hothorn [cre, aut] (ORCID: ), Peter Buehlmann [aut] (ORCID: ), Thomas Kneib [aut] (ORCID: ), Matthias Schmid [aut] (ORCID: ), Benjamin Hofner [aut] (ORCID: ), Fabian Otto-Sobotka [ctb] (ORCID: ), Fabian Scheipl [ctb] (ORCID: ), Andreas Mayr [ctb] (ORCID: ) Maintainer: Torsten Hothorn