gpboost: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models

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 <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2020) <arXiv:2004.02653> and Sigrist (2021) <arXiv:2105.08966> for more information on the methodology.

Getting started

Package details

AuthorFabio Sigrist [aut, cre], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the included version of Eigen [ctb, cph], Timothy A. Davis [cph], Guolin Ke [ctb], Damien Soukhavong [ctb], James Lamb [ctb], Other authors of LightGBM for the included version of LightGBM [ctb], Microsoft Corporation [cph], Dropbox, Inc. [cph], Jay Loden [cph], Dave Daeschler [cph], Giampaolo Rodola [cph], Alberto Ferreira [ctb], Daniel Lemire [ctb], Victor Zverovich [cph], IBM Corporation [ctb], Keith O'Hara [cph], Stephen L. Moshier [cph]
MaintainerFabio Sigrist <fabiosigrist@gmail.com>
LicenseApache License (== 2.0) | file LICENSE
Version0.6.6
URL https://github.com/fabsig/GPBoost
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("gpboost")

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gpboost documentation built on July 14, 2021, 9:06 a.m.