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# `rrcov`: Scalable Robust Estimators with High Breakdown Point [](https://cran.r-project.org/package=rrcov) [](https://github.com/valentint/rrcov/actions) [](https://cran.r-project.org/package=rrcov) [](https://cran.r-project.org/package=rrcov) [](https://www.gnu.org/licenses/gpl-3.0.en.html) The package `rrcov` provides scalable robust estimators with high breakdown point and covers a large number of robustified multivariate analysis methods, starting with robust estimators for the multivariate location and covariance matrix (MCD, MVE, S, MM, SD), the deterministic versions of MCD, S and MM estimates and regularized versions (MRCD) for high dimensions. These estimators are used to conduct robust principal components analysis (`PcaCov()`), linear and quadratic discriminant analysis (`Linda()`, `Qda()`), MANOVA. Projection pursuit algorithms for PCA to be applied in high dimensions are also available (`PcaHubert()`, `PcaGrid()` and `PcaProj()`). ## Installation The `rrcov` package is on CRAN (The Comprehensive R Archive Network) and the latest release can be easily installed using the command install.packages("rrcov") library(rrcov) ## 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/rrcov", build_opts = c("--no-build-vignettes")) Of course, if you have already installed `remotes`, you can skip the first line (I have commented it out). ## Example This is a basic example which shows you if the package is properly installed: ``` r library(rrcov) #> Loading required package: robustbase #> Scalable Robust Estimators with High Breakdown Point (version 1.7-3) data(hbk) (out <- CovMcd(hbk)) #> #> Call: #> CovMcd(x = hbk) #> -> Method: Fast MCD(alpha=0.5 ==> h=40); nsamp = 500; (n,k)mini = (300,5) #> #> Robust Estimate of Location: #> X1 X2 X3 Y #> 1.55833 1.80333 1.66000 -0.08667 #> #> Robust Estimate of Covariance: #> X1 X2 X3 Y #> X1 1.58739 0.03129 0.21694 0.10748 #> X2 0.03129 1.60733 0.25612 0.02864 #> X3 0.21694 0.25612 1.47254 -0.18174 #> Y 0.10748 0.02864 -0.18174 0.44081 ``` ## 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*](https://github.com/valentint/rrcov/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.

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