Robust Regression with Compositional Covariates [R package robregcc version 1.1]

Aditya Mishra

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) <doi:10.48550/arXiv.1909.04990>.

Version: 1.1

Depends: R (≥ 3.5.0), stats, utils

Imports: Rcpp (≥ 0.12.0), MASS, magrittr, graphics

LinkingTo: Rcpp, RcppArmadillo

Published: 2020年07月25日

DOI: 10.32614/CRAN.package.robregcc

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-stats/robregcc

NeedsCompilation: yes

In views: CompositionalData

CRAN checks: robregcc results

Documentation:

Reference manual: robregcc.html , robregcc.pdf

Downloads:

Package source: robregcc_1.1.tar.gz

Windows binaries: r-devel: robregcc_1.1.zip, r-release: robregcc_1.1.zip, r-oldrel: robregcc_1.1.zip

macOS binaries: r-release (arm64): robregcc_1.1.tgz, r-oldrel (arm64): robregcc_1.1.tgz, r-release (x86_64): robregcc_1.1.tgz, r-oldrel (x86_64): robregcc_1.1.tgz

Old sources: robregcc archive

Linking:

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