Package: ClustImpute
Type: Package
Title: K-Means Clustering with Build-in Missing Data Imputation
Version: 0.2.4
Author: Oliver Pfaffel
Maintainer: Oliver Pfaffel <opfaffel@gmail.com>
Description: This k-means algorithm is able to cluster data with
        missing values and as a by-product completes the data set. The
        implementation can deal with missing values in multiple
        variables and is computationally efficient since it iteratively
        uses the current cluster assignment to define a plausible
        distribution for missing value imputation. Weights are used to
        shrink early random draws for missing values (i.e., draws based
        on the cluster assignments after few iterations) towards the
        global mean of each feature. This shrinkage slowly fades out
        after a fixed number of iterations to reflect the increasing
        credibility of cluster assignments. See the vignette for
        details.
License: GPL-3
Encoding: UTF-8
Imports: ClusterR, copula, dplyr, magrittr, tidyr, ggplot2, rlang,
        knitr
Suggests: ggExtra, rmarkdown, testthat (>= 2.1.0), Hmisc, tictoc,
        spelling, corrplot, covr
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Language: en-US
Config/pak/sysreqs: libgmp3-dev libgsl0-dev libicu-dev
Repository: https://o1iv3r.r-universe.dev
Date/Publication: 2021-09-26 19:22:07 UTC
RemoteUrl: https://github.com/o1iv3r/clustimpute
RemoteRef: HEAD
RemoteSha: 9a0694f368c2e7342b7604fdac0eb5321b7c5917
NeedsCompilation: no
Packaged: 2026-09-27 07:01:28 UTC; root