rrcovHD: Robust Multivariate Methods for High Dimensional Data

Robust multivariate methods for high dimensional data including outlier detection (Filzmoser and Todorov (2013) <doi:10.1016/j.ins.2012.10.017>), robust sparse PCA (Croux et al. (2013) <doi:10.1080/00401706.2012.727746>, Todorov and Filzmoser (2013) <doi:10.1007/978-3-642-33042-1_31>), robust PLS (Todorov and Filzmoser (2014) <doi:10.17713/ajs.v43i4.44>), and robust sparse classification (Ortner et al. (2020) <doi:10.1007/s10618-019-00666-8>).

Version: 0.2-7
Depends: rrcov (≥ 1.3-7), robustbase (≥ 0.92-1), methods
Imports: stats4, pls, spls, pcaPP, robustHD, Rcpp
LinkingTo: Rcpp
Suggests: MASS
Published: 2021-04-23
Author: Valentin Todorov ORCID iD [aut, cre]
Maintainer: Valentin Todorov <valentin.todorov at chello.at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: ChangeLog
In views: Robust
CRAN checks: rrcovHD results


Reference manual: rrcovHD.pdf
Package source: rrcovHD_0.2-7.tar.gz
Windows binaries: r-devel: rrcovHD_0.2-7.zip, r-release: rrcovHD_0.2-7.zip, r-oldrel: rrcovHD_0.2-7.zip
macOS binaries: r-release: rrcovHD_0.2-7.tgz, r-oldrel: rrcovHD_0.2-7.tgz
Old sources: rrcovHD archive

Reverse dependencies:

Reverse imports: rospca


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