FastHCS: Robust Algorithm for Principal Component Analysis

The FastHCS algorithm of Schmitt and Vakili (2015) for high-dimensional, robust PCA modelling and associated outlier detection and diagnostic tools.

Version: 0.0.7
Depends: R (≥ 3.1.1), matrixStats
Imports: methods
LinkingTo: Rcpp, RcppEigen
Published: 2020-05-10
Author: Kaveh Vakili [aut, cre]
Maintainer: Kaveh Vakili <vakili.kaveh.email at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: FastHCS results

Documentation:

Reference manual: FastHCS.pdf

Downloads:

Package source: FastHCS_0.0.7.tar.gz
Windows binaries: r-devel: FastHCS_0.0.7.zip, r-devel-UCRT: FastHCS_0.0.7.zip, r-release: FastHCS_0.0.7.zip, r-oldrel: FastHCS_0.0.7.zip
macOS binaries: r-release (arm64): FastHCS_0.0.7.tgz, r-release (x86_64): FastHCS_0.0.7.tgz, r-oldrel: FastHCS_0.0.7.tgz
Old sources: FastHCS archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FastHCS to link to this page.