Package: erboost 1.5

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.

Authors:Yi Yang [aut, cre], Hui Zou [aut], Greg Ridgeway [ctb, cph]

erboost_1.5.tar.gz
erboost_1.5.zip(r-4.7)erboost_1.5.zip(r-4.6)erboost_1.5.zip(r-4.5)
erboost_1.5.tgz(r-4.6-x86_64)erboost_1.5.tgz(r-4.6-arm64)erboost_1.5.tgz(r-4.5-x86_64)erboost_1.5.tgz(r-4.5-arm64)
erboost_1.5.tar.gz(r-4.7-arm64)erboost_1.5.tar.gz(r-4.7-x86_64)erboost_1.5.tar.gz(r-4.6-arm64)erboost_1.5.tar.gz(r-4.6-x86_64)
erboost_1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
erboost/json (API)

# Install 'erboost' in R:
install.packages('erboost', repos = c('https://archer-yang-lab.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 1 scripts 196 downloads 10 exports 1 dependencies

Last updated from:cc67e5dc32. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK123
linux-devel-x86_64OK103
source / vignettesOK156
linux-release-arm64OK108
linux-release-x86_64OK92
macos-release-arm64OK92
macos-release-x86_64OK152
macos-oldrel-arm64OK105
macos-oldrel-x86_64OK182
windows-develOK81
windows-releaseOK99
windows-oldrelOK91
wasm-releaseOK108

Exports:erboosterboost.fiterboost.losserboost.moreerboost.perfpermutation.test.erboostplot.erboostpredict.erboostrelative.influencesummary.erboost

Dependencies:lattice