enpls: Ensemble Partial Least Squares Regression

An algorithmic framework for measuring feature importance, outlier detection, model applicability domain evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.

Version: 5.9
Depends: R (≥ 3.0.2)
Imports: pls, spls, foreach, doParallel, ggplot2, reshape2, plotly
Suggests: knitr, rmarkdown
Published: 2017-09-27
Author: Nan Xiao [aut, cre], Dong-Sheng Cao [aut], Miao-Zhu Li [aut], Qing-Song Xu [aut]
Maintainer: Nan Xiao <me at nanx.me>
BugReports: https://github.com/road2stat/enpls/issues
License: GPL-3 | file LICENSE
URL: https://enpls.org, https://github.com/road2stat/enpls
NeedsCompilation: no
Materials: README NEWS
In views: ChemPhys
CRAN checks: enpls results

Downloads:

Reference manual: enpls.pdf
Vignettes: A Brief Introduction to enpls
Package source: enpls_5.9.tar.gz
Windows binaries: r-devel: enpls_5.9.zip, r-release: enpls_5.9.zip, r-oldrel: enpls_5.9.zip
OS X El Capitan binaries: r-release: enpls_5.9.tgz
OS X Mavericks binaries: r-oldrel: enpls_5.9.tgz
Old sources: enpls archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=enpls to link to this page.