The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

robustlm: Robust Variable Selection with Exponential Squared Loss

Computationally efficient tool for performing variable selection and obtaining robust estimates, which implements robust variable selection procedure proposed by Wang, X., Jiang, Y., Wang, S., Zhang, H. (2013) <doi:10.1080/01621459.2013.766613>. Users can enjoy the near optimal, consistent, and oracle properties of the procedures.

Version: 0.1.0
Imports: MASS, matrixStats
Suggests: knitr, rmarkdown
Published: 2021-03-22
DOI: 10.32614/CRAN.package.robustlm
Author: Jin Zhu ORCID iD [cre, aut], Borui Tang [aut], Yunlu Jiang [aut], Xueqin Wang ORCID iD [aut]
Maintainer: Jin Zhu <zhuj37 at mail2.sysu.edu.cn>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: robustlm results

Documentation:

Reference manual: robustlm.pdf
Vignettes: Robust Variable Selection with Exponential Squared Loss

Downloads:

Package source: robustlm_0.1.0.tar.gz
Windows binaries: r-devel: robustlm_0.1.0.zip, r-release: robustlm_0.1.0.zip, r-oldrel: robustlm_0.1.0.zip
macOS binaries: r-release (arm64): robustlm_0.1.0.tgz, r-oldrel (arm64): robustlm_0.1.0.tgz, r-release (x86_64): robustlm_0.1.0.tgz, r-oldrel (x86_64): robustlm_0.1.0.tgz

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.