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gpboost
Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
View on CRAN: Click
here
Download and install gpboost package within the R console
Install from CRAN:
install.packages("gpboost")
Install from Github:
library("remotes")
install_github("cran/gpboost") Install by package version:
library("remotes")
install_version("gpboost", "1.7.4") Attach the package and use:
library("gpboost")
Maintained by
Fabio Sigrist
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-17
Latest Update: 2025-07-23
Description:
An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See for more information on the software and Sigrist (2022, JMLR) and Sigrist (2023, TPAMI) for more information on the methodology.
How to cite:
Fabio Sigrist (2021). gpboost: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models. R package version 1.7.4, https://cran.r-project.org/web/packages/gpboost. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-08-23 12:41), 0.4.0 (2021-02-17 21:20), 0.5.0 (2021-03-12 14:20), 0.6.0 (2021-04-21 14:50), 0.6.1 (2021-05-25 12:00), 0.6.3 (2021-06-18 11:00), 0.6.6 (2021-07-14 09:30), 0.6.7 (2021-08-17 18:20), 0.7.0 (2021-12-09 21:50), 0.7.1 (2022-01-15 13:22), 0.7.2 (2022-02-21 12:10), 0.7.3.1 (2022-03-23 14:20), 0.7.3 (2022-03-22 17:20), 0.7.5 (2022-05-05 11:30), 0.7.6.2 (2022-05-09 10:40), 0.7.7 (2022-06-10 15:40), 0.7.8 (2022-07-08 16:00), 0.7.9 (2022-08-25 14:40), 0.7.10 (2022-11-14 09:20), 0.8.0 (2022-12-01 17:40), 0.8.1 (2023-01-19 07:40), 0.8.2 (2023-02-17 18:20), 1.0.0 (2023-03-09 15:00), 1.0.1 (2023-03-10 12:10), 1.2.0 (2023-06-09 15:30), 1.2.1 (2023-06-15 01:20), 1.2.3 (2023-07-16 08:00), 1.2.4 (2023-10-02 17:30), 1.2.5 (2023-10-04 17:40), 1.2.6 (2023-10-24 10:10), 1.2.7 (2023-11-29 17:20), 1.2.8 (2024-01-19 01:10), 1.2.9 (2024-02-19 17:30), 1.3.0 (2024-02-28 09:30), 1.3.1 (2024-03-28 09:40), 1.4.0.1 (2024-04-15 08:40), 1.4.0 (2024-04-11 17:50), 1.5.0 (2024-05-28 11:00), 1.5.1.1 (2024-07-16 17:10), 1.5.1.2 (2024-08-26 20:20), 1.5.1 (2024-06-21 15:40), 1.5.4 (2024-11-15 18:40), 1.5.5.1 (2025-01-20 11:00), 1.5.5 (2024-12-20 17:30), 1.5.6 (2025-02-19 08:20), 1.5.7 (2025-05-13 17:20), 1.5.8 (2025-05-14 13:30), 1.6.0 (2025-07-22 16:20), 1.6.1 (2025-07-23 10:30), 1.6.2 (2025-08-27 16:20), 1.6.3 (2025-10-10 08:50), 1.6.4 (2025-11-07 15:50), 1.6.5 (2026-01-08 18:30), 1.6.6 (2026-02-11 15:30), 1.6.7 (2026-04-27 09:30), 1.6.8 (2026-06-24 20:10), 1.7.0.1 (2026-07-13 16:00), 1.7.0 (2026-07-10 12:10), 1.7.1.1 (2026-07-23 12:30), 1.7.1 (2026-07-22 19:10), 1.7.2 (2026-08-20 00:20)
Other packages that cited gpboost R package
View gpboost citation profile
Other R packages that gpboost depends,
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Complete documentation for gpboost
Functions, R codes and Examples using
the gpboost R package
Some associated functions: GPBoost_data . GPModel . GPModel_shared_params . X . X_test . agaricus.test . agaricus.train . bank . coords . coords_test . dim . dimnames.gpb.Dataset . fit.GPModel . fit . fitGPModel . get_nested_categories . getinfo . gpb.Dataset.construct . gpb.Dataset.create.valid . gpb.Dataset . gpb.Dataset.save . gpb.Dataset.set.categorical . gpb.Dataset.set.reference . gpb.convert_with_rules . gpb.cv . gpb.dump . gpb.get.eval.result . gpb.grid.search.tune.parameters . gpb.importance . gpb.interprete . gpb.load . gpb.model.dt.tree . gpb.plot.importance . gpb.plot.interpretation . gpb.plot.part.dep.interact . gpb.plot.partial.dependence . gpb.save . gpb.train . gpb_shared_params . gpboost . group_data . group_data_test . loadGPModel . neg_log_likelihood.GPModel . neg_log_likelihood . predict.GPModel . predict.gpb.Booster . predict_training_data_random_effects.GPModel . predict_training_data_random_effects . readRDS.gpb.Booster . saveGPModel . saveRDS.gpb.Booster . set_optim_params.GPModel . set_optim_params . set_prediction_data.GPModel . set_prediction_data . setinfo . slice . summary.GPModel . y .
Some associated R codes: GPModel.R . aliases.R . callback.R . gpb.Booster.R . gpb.Dataset.R . gpb.Predictor.R . gpb.convert_with_rules.R . gpb.cv.R . gpb.importance.R . gpb.interprete.R . gpb.model.dt.tree.R . gpb.plot.importance.R . gpb.plot.interpretation.R . gpb.plot.partial.dependence.R . gpb.train.R . gpboost.R . metrics.R . readRDS.gpb.Booster.R . saveRDS.gpb.Booster.R . utils.R . Full gpboost package functions and examples
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