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Nonparametric Multiple Expectile Regression via ER-Boost

v1.5 · Mar 25, 2025 · GPL-3

Description

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.

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
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r-patched-linux-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies lattice erboost

Version History

new 1.5 Mar 10, 2026
updated 1.5 ← 1.4 diff Mar 24, 2025
new 1.4 Jan 18, 2024