ClustImpute: K-means clustering with build-in missing data imputation

This clustering algorithm deals with missing data via weights that are imposed on missings and successively increased. See the vignette for details.

Version: 0.1.7
Imports: ClusterR, copula, dplyr, magrittr, rlang
Suggests: ggExtra, ggplot2, knitr, rmarkdown, testthat (≥ 2.1.0), tidyr, Hmisc, tictoc, spelling, corrplot, covr
Published: 2021-01-06
Author: Oliver Pfaffel
Maintainer: Oliver Pfaffel <opfaffel at gmail.com>
License: GPL-3
NeedsCompilation: no
Language: en-US
Citation: ClustImpute citation info
Materials: README NEWS
In views: MissingData
CRAN checks: ClustImpute results

Downloads:

Reference manual: ClustImpute.pdf
Vignettes: Example_on_simulated_data
Description of the algorithm
Package source: ClustImpute_0.1.7.tar.gz
Windows binaries: r-devel: ClustImpute_0.1.7.zip, r-release: ClustImpute_0.1.7.zip, r-oldrel: ClustImpute_0.1.7.zip
macOS binaries: r-release: ClustImpute_0.1.7.tgz, r-oldrel: ClustImpute_0.1.7.tgz
Old sources: ClustImpute archive

Reverse dependencies:

Reverse suggests: FeatureImpCluster

Linking:

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