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robust: Port of the S+ “Robust Library”

This package contains the Robust Library version 0.4

• Contributors:
  • Jeff Wang jwang@statsci.com
  • Ruben Zamar ruben@stat.ubc.ca
  • Alfio Marazzi Alfio.Marazzi@inst.hospvd.ch
  • Victor Yohai vyohai@dm.uba.ar
  • Matias Salibian-Barrera matias@stat.ubc.ca
  • Ricardo Maronna maron@mate.unlp.edu.ar
  • Eric Zivot ezivot@u.washington.edu
  • David Rocke dmrocke@ucdavis.edu
  • Doug Martin doug@statsci.com
  • Kjell Konis kjell.konis@icloud.com

• This package contains the following robust methods:
  • Robust Covariance estimation (scatter and location)
  • Robust Linear Regression
  • Robust Generalized Linear Models
  • Robust Gamma, Weibull, and lognormal parameter estimation
• A method for side-by-side comparison of robust and classical models is also provided. Please see Robust.pdf for further details.

Installation

The robust package is on CRAN (The Comprehensive R Archive Network) and the latest release can be easily installed using the command

install.packages("robust")

Building from source

To install the latest stable development version from GitHub, you can pull this repository and install it using

## install.packages("remotes")
remotes::install_github("valentint/robust")

Of course, if you have already installed remotes, you can skip the first line (I have commented it out).

Community guidelines

Report issues and request features

If you experience any bugs or issues or if you have any suggestions for additional features, please submit an issue via the Issues tab of this repository. Please have a look at existing issues first to see if your problem or feature request has already been discussed.

Contribute to the package

If you want to contribute to the package, you can fork this repository and create a pull request after implementing the desired functionality.

Ask for help

If you need help using the package, or if you are interested in collaborations related to this project, please get in touch with the package maintainer.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.