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) for more information on the methodology.


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Reference manual

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install.packages("gpboost")

0.6.0 by Fabio Sigrist, 2 days ago


https://github.com/fabsig/GPBoost


Report a bug at https://github.com/fabsig/GPBoost/issues


Browse source code at https://github.com/cran/gpboost


Authors: Fabio 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]


Documentation:   PDF Manual  


Apache License (== 2.0) | file LICENSE license


Imports data.table, graphics, RJSONIO, Matrix, methods, utils

Depends on R6

Suggests testthat

System requirements: C++11


See at CRAN