The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
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[@]dogado.de.

qVarSel: Select Variables for Optimal Clustering

Finding hidden clusters in structured data can be hindered by the presence of masking variables. If not detected, masking variables are used to calculate the overall similarities between units, and therefore the cluster attribution is more imprecise. The algorithm q-vars implements an optimization method to find the variables that most separate units between clusters. In this way, masking variables can be discarded from the data frame and the clustering is more accurate. Tests can be found in Benati et al.(2017) <doi:10.1080/01605682.2017.1398206>.

Version: 1.1
Imports: Rcpp (≥ 1.0.13), lpSolveAPI
LinkingTo: Rcpp
Suggests: mclust
Published: 2024-11-28
DOI: 10.32614/CRAN.package.qVarSel
Author: Stefano Benati ORCID iD [aut, cre]
Maintainer: Stefano Benati <stefano.benati at unitn.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: qVarSel results

Documentation:

Reference manual: qVarSel.pdf

Downloads:

Package source: qVarSel_1.1.tar.gz
Windows binaries: r-devel: qVarSel_1.1.zip, r-release: qVarSel_1.1.zip, r-oldrel: qVarSel_1.1.zip
macOS binaries: r-release (arm64): qVarSel_1.1.tgz, r-oldrel (arm64): qVarSel_1.1.tgz, r-release (x86_64): qVarSel_1.1.tgz, r-oldrel (x86_64): qVarSel_1.1.tgz
Old sources: qVarSel archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=qVarSel 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.
Health stats visible at Monitor.