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 |
| 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 |
| CRAN checks: | robregcc results |
| Reference manual: | robregcc.pdf |
| Package source: | robregcc_1.1.tar.gz |
| Windows binaries: | r-prerel: robregcc_1.1.zip, r-release: robregcc_1.1.zip, r-oldrel: robregcc_1.1.zip |
| macOS binaries: | r-prerel (arm64): robregcc_1.1.tgz, r-release (arm64): robregcc_1.1.tgz, r-oldrel (arm64): robregcc_1.1.tgz, r-prerel (x86_64): robregcc_1.1.tgz, r-release (x86_64): robregcc_1.1.tgz |
| Old sources: | robregcc archive |
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