The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

epca: Exploratory Principal Component Analysis

Exploratory principal component analysis for large-scale dataset, including sparse principal component analysis and sparse matrix approximation.

Version: 1.1.0
Depends: R (≥ 3.5)
Imports: clue, irlba, Matrix, GPArotation
Suggests: elasticnet, ggcorrplot, tidyverse, rmarkdown, reshape2, markdown, RSpectra, matlabr, knitr, PMA, testthat (≥ 3.0.0)
Published: 2023-07-10
Author: Fan Chen ORCID iD [aut, cre]
Maintainer: Fan Chen <fan.chen at wisc.edu>
BugReports: https://github.com/fchen365/epca/issues
License: GPL-3
URL: https://github.com/fchen365/epca
NeedsCompilation: no
Materials: README NEWS
CRAN checks: epca results

Documentation:

Reference manual: epca.pdf
Vignettes: Explore multivariate data with 'epca'

Downloads:

Package source: epca_1.1.0.tar.gz
Windows binaries: r-devel: epca_1.1.0.zip, r-release: epca_1.1.0.zip, r-oldrel: epca_1.1.0.zip
macOS binaries: r-release (arm64): epca_1.1.0.tgz, r-oldrel (arm64): epca_1.1.0.tgz, r-release (x86_64): epca_1.1.0.tgz, r-oldrel (x86_64): epca_1.1.0.tgz
Old sources: epca archive

Reverse dependencies:

Reverse suggests: gdim

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.