Package: rrat 1.0.0

Yi He

rrat: Robust Regression with Asymmetric Heavy-Tail Noise Distributions

Implementation of Robust Regression tailored to deal with Asymmetric noise Distribution, which was originally proposed by Takeuchi & Bengio & Kanamori (2002) <doi:10.1162/08997660260293300>. In addition, this implementation is extended as introducing potential feature regularization by LASSO etc.

Authors:Yi He and Yuelin Zhao

rrat_1.0.0.tar.gz
rrat_1.0.0.tar.gz(r-4.5-noble)rrat_1.0.0.tar.gz(r-4.4-noble)
rrat_1.0.0.tgz(r-4.4-emscripten)rrat_1.0.0.tgz(r-4.3-emscripten)
rrat.pdf |rrat.html✨
rrat/json (API)

# Install 'rrat' in R:
install.packages('rrat', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 129 downloads 1 exports 7 dependencies

Last updated 5 years agofrom:0ff6fcb9c0. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 11 2025
R-4.5-linuxOKMar 11 2025
R-4.4-linuxOKMar 11 2025

Exports:rrat

Dependencies:latticeMASSMatrixMatrixModelsquantregSparseMsurvival

Citation

To cite package ‘rrat’ in publications use:

He Y, Zhao Y (2019). rrat: Robust Regression with Asymmetric Heavy-Tail Noise Distributions. R package version 1.0.0, https://CRAN.R-project.org/package=rrat.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {rrat: Robust Regression with Asymmetric Heavy-Tail Noise
      Distributions},
    author = {Yi He and Yuelin Zhao},
    year = {2019},
    note = {R package version 1.0.0},
    url = {https://CRAN.R-project.org/package=rrat},
  }