erboost: Nonparametric Multiple Expectile Regression via ER-Boost

Expectile regression is a nice tool for estimating the conditional expectiles of a response variable given a set of covariates. This package implements a regression tree based gradient boosting estimator for nonparametric multiple expectile regression, proposed by Yang, Y., Qian, W. and Zou, H. (2018) <doi:10.1080/00949655.2013.876024>. The code is based on the 'gbm' package originally developed by Greg Ridgeway.

Version: 1.4
Depends: R (≥ 2.12.0), lattice, splines
Published: 2024-01-19
DOI: 10.32614/CRAN.package.erboost
Author: Yi Yang [aut, cre] (, Hui Zou [aut] (, Greg Ridgeway [ctb, cph]
Maintainer: Yi Yang <yi.yang6 at>
License: GPL-3
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: erboost results


Reference manual: erboost.pdf


Package source: erboost_1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): erboost_1.4.tgz, r-oldrel (arm64): erboost_1.4.tgz, r-release (x86_64): erboost_1.4.tgz, r-oldrel (x86_64): erboost_1.4.tgz


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