Package: qVarSel 1.1

Stefano Benati

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>.

Authors:Stefano Benati [aut, cre]

qVarSel_1.1.tar.gz
qVarSel_1.1.zip(r-4.5)qVarSel_1.1.zip(r-4.4)qVarSel_1.1.zip(r-4.3)
qVarSel_1.1.tgz(r-4.4-x86_64)qVarSel_1.1.tgz(r-4.4-arm64)qVarSel_1.1.tgz(r-4.3-x86_64)qVarSel_1.1.tgz(r-4.3-arm64)
qVarSel_1.1.tar.gz(r-4.5-noble)qVarSel_1.1.tar.gz(r-4.4-noble)
qVarSel_1.1.tgz(r-4.4-emscripten)qVarSel_1.1.tgz(r-4.3-emscripten)
qVarSel.pdf |qVarSel.html
qVarSel/json (API)

# Install 'qVarSel' in R:
install.packages('qVarSel', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

archivedpackagesr-universecpp

1.70 score 5 stars 4 scripts 101 downloads 3 exports 2 dependencies

Last updated 25 days agofrom:2341aa3b07 (on package/qVarSel). Checks:9 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 09 2025
R-4.5-win-x86_64OKJan 09 2025
R-4.5-linux-x86_64OKJan 09 2025
R-4.4-win-x86_64OKJan 09 2025
R-4.4-mac-x86_64OKJan 09 2025
R-4.4-mac-aarch64OKJan 09 2025
R-4.3-win-x86_64OKJan 09 2025
R-4.3-mac-x86_64OKJan 09 2025
R-4.3-mac-aarch64OKJan 09 2025

Exports:PrtDistqVarSelHqVarSelLP

Dependencies:lpSolveAPIRcpp