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-release: FastHCS_0.0.7.zip, r-oldrel: FastHCS_0.0.7.zip
macOS binaries:	r-release (arm64): FastHCS_0.0.7.tgz, r-oldrel (arm64): FastHCS_0.0.7.tgz, r-release (x86_64): FastHCS_0.0.7.tgz, r-oldrel (x86_64): FastHCS_0.0.7.tgz
Old sources:	FastHCS archive

Linking:

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