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.tar.gz(r-4.5-noble)robregcc_1.1.tar.gz(r-4.4-noble)
robregcc_1.1.tgz(r-4.4-emscripten)robregcc_1.1.tgz(r-4.3-emscripten)
robregcc.pdf |robregcc.html✨
robregcc/json (API)

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

Peer review:

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).

openblascpp

1.63 score 43 scripts 115 downloads 10 exports 4 dependencies

Last updated 4 years agofrom:3ba1185aba. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 22 2024
R-4.5-linux-x86_64OKDec 22 2024

Exports:classoclasso_pathcoef_cccpsc_spplot_cvplot_pathplot_residrobregcc_optionrobregcc_simrobregcc_sp

Dependencies:magrittrMASSRcppRcppArmadillo