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: 2020-07-25 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.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:Please use the canonical form https://CRAN.R-project.org/package=robregcc to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4