rrat: Robust Regression with Asymmetric Heavy-Tail Noise Distributions

Implementation of Robust Regression tailored to deal with Asymmetric noise Distribution, which was originally proposed by Takeuchi & Bengio & Kanamori (2002) <doi:10.1162/08997660260293300>. In addition, this implementation is extended as introducing potential feature regularization by LASSO etc.

Version: 1.0.0
Depends: R (≥ 2.10), quantreg
Published: 2019-10-07
Author: Yi He and Yuelin Zhao
Maintainer: Yi He <yi.he at stats.oxon.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: rrat results


Reference manual: rrat.pdf
Package source: rrat_1.0.0.tar.gz
Windows binaries: r-devel: rrat_1.0.0.zip, r-release: rrat_1.0.0.zip, r-oldrel: rrat_1.0.0.zip
macOS binaries: r-release (arm64): rrat_1.0.0.tgz, r-release (x86_64): rrat_1.0.0.tgz, r-oldrel: rrat_1.0.0.tgz


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