<p>A matrix with covariate data for the example data of the GPBoost package</p>

datasets

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 (2022, JMLR) <https://www.jmlr.org/papers/v23/20-322.html> and Sigrist (2023, TPAMI) <doi:10.1109/TPAMI.2022.3168152> for more information on the methodology.

Fabio Sigrist

gpboost

Combining Tree-Boosting with Gaussian Process and Mixed Effects
Models

Tim Gyger

Pascal Kuendig

Benoit Jacob

Gael Guennebaud

Nicolas Carre

Pierre Zoppitelli

Gauthier Brun

Jean Ceccato

Jitse Niesen

Other authors of Eigen for the included version of Eigen 

Timothy A. Davis

Guolin Ke

Damien Soukhavong

James Lamb

Other authors of LightGBM for the included version of LightGBM 

Microsoft Corporation 

Dropbox, Inc. 

Jay Loden

Dave Daeschler

Giampaolo Rodola

Alberto Ferreira

Daniel Lemire

Victor Zverovich

IBM Corporation 

Keith O'Hara 

Stephen L. Moshier 

Jorge Nocedal 

Naoaki Okazaki 

Yixuan Qiu 

Dirk Toewe 

X function

Predictor variable data for example data for the GPBoost package — X

Predictor variable data for example data for the GPBoost package

X: Predictor variable data for example data for the GPBoost package

Description

Usage

Arguments