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: |
1.5 |
| Depends: |
R (≥ 2.12.0), lattice, splines |
| Published: |
2025-03-25 |
| DOI: |
10.32614/CRAN.package.erboost |
| Author: |
Yi Yang [aut, cre] (http://www.math.mcgill.ca/yyang/),
Hui Zou [aut] (http://users.stat.umn.edu/~zouxx019/),
Greg Ridgeway [ctb, cph] |
| Maintainer: |
Yi Yang <yi.yang6 at mcgill.ca> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| Materials: |
ChangeLog |
| CRAN checks: |
erboost results |
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