GraphPCA: Graphical Tools of Histogram PCA

Histogram principal components analysis is the generalization of the PCA. Histogram data are adapted to design complex and big data which histograms used as variables (big data adapter). Functions implemented provides numerical and graphical tools of an extension of PCA. Sun Makosso Kallyth (2016) <doi:10.1002/sam.11270>. Sun Makosso Kallyth and Edwin Diday (2012) <doi:10.1007/s11634-012-0108-0>.

Version: 1.1
Depends: R (≥ 2.15.1)
Imports: ggplot2, FactoMineR, scatterplot3d, ggplot2movies
Published: 2018-04-13
Author: Brahim Brahim and Sun Makosso-Kallyth
Maintainer: Brahim Brahim <brahim.brahim at bigdatavisualizations.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: GraphPCA results

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Reference manual: GraphPCA.pdf
Package source: GraphPCA_1.1.tar.gz
Windows binaries: r-prerel: GraphPCA_1.1.zip, r-release: GraphPCA_1.1.zip, r-oldrel: GraphPCA_1.1.zip
OS X binaries: r-prerel: GraphPCA_1.1.tgz, r-release: GraphPCA_1.1.tgz
Old sources: GraphPCA archive

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