robregcc: Robust Regression with Compositional Covariates

We implement the algorithm estimating the parameters of the robust regression model with compositional covariates. The model simultaneously treats outliers and provides reliable parameter estimates. Publication reference: Mishra, A., Mueller, C.,(2019) <arXiv:1909.04990>.

Version: 1.0
Depends: R (≥ 3.5.0), stats, utils
Imports: Rcpp (≥ 0.12.0), MASS, magrittr, graphics
LinkingTo: Rcpp, RcppArmadillo
Published: 2019-10-14
Author: Aditya Mishra [aut, cre], Christian Muller [ctb]
Maintainer: Aditya Mishra <amishra at flatironinstitute.org>
License: GPL (≥ 3.0)
URL: https://arxiv.org/abs/1909.04990, https://github.com/amishra-simonsfoundation/robregcc
NeedsCompilation: yes
CRAN checks: robregcc results

Downloads:

Reference manual: robregcc.pdf
Package source: robregcc_1.0.tar.gz
Windows binaries: r-devel: robregcc_1.0.zip, r-devel-gcc8: robregcc_1.0.zip, r-release: robregcc_1.0.zip, r-oldrel: robregcc_1.0.zip
OS X binaries: r-release: robregcc_1.0.tgz, r-oldrel: robregcc_1.0.tgz

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