Package: robregcc 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) <arxiv:1909.04990>.

Authors:Aditya Mishra [aut, cre], Christian Muller [ctb]

robregcc_1.1.tar.gz
robregcc_1.1.zip(r-4.7-x86_64)robregcc_1.1.zip(r-4.7-arm64)robregcc_1.1.zip(r-4.6-x86_64)robregcc_1.1.zip(r-4.6-arm64)
robregcc_1.1.tar.gz(r-4.7-arm64)robregcc_1.1.tar.gz(r-4.7-x86_64)robregcc_1.1.tar.gz(r-4.6-arm64)robregcc_1.1.tar.gz(r-4.6-x86_64)
robregcc_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
robregcc/json (API)

# Install 'robregcc' in R:
install.packages('robregcc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/amishra-stats/robregcc/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • simulate_robregcc - Simulated date for testing functions in the robregcc package (sparse setting).

On CRAN:

Conda:

openblascpp

1.46 score 29 scripts 240 downloads 10 exports 4 dependencies

Last updated from:3ba1185aba. Checks:6 OK, 4 NOTE. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK192
linux-devel-x86_64OK189
source / vignettesOK165
linux-release-arm64OK210
linux-release-x86_64OK139
windows-devel-arm64NOTE238
windows-devel-x86_64NOTE260
windows-release-arm64NOTE231
windows-release-x86_64NOTE223
wasm-releaseOK158

Exports:classoclasso_pathcoef_cccpsc_spplot_cvplot_pathplot_residrobregcc_optionrobregcc_simrobregcc_sp

Dependencies:magrittrMASSRcppRcppArmadillo