VIM: Visualization and Imputation of Missing Values (original) (raw)

New tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and allows to explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface available in the separate package VIMGUI allows an easy handling of the implemented plot methods.

Version: 6.2.2
Depends: R (≥ 3.5.0), colorspace, grid
Imports: car, grDevices, magrittr, robustbase, stats, sp, vcd, MASS, nnet, e1071, methods, Rcpp, utils, graphics, laeken, ranger, data.table (≥ 1.9.4)
LinkingTo: Rcpp
Suggests: dplyr, tinytest, knitr, rmarkdown, reactable, covr, withr
Published: 2022-08-25
DOI: 10.32614/CRAN.package.VIM
Author: Matthias Templ [aut, cre], Alexander Kowarik ORCID iD [aut], Andreas Alfons [aut], Gregor de Cillia [aut], Bernd Prantner [ctb], Wolfgang Rannetbauer [aut]
Maintainer: Matthias Templ <matthias.templ at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/statistikat/VIM
NeedsCompilation: yes
Citation: VIM citation info
Materials: NEWS
In views: MissingData, OfficialStatistics
CRAN checks: VIM results

Documentation:

Downloads:

Reverse dependencies:

Reverse imports: destiny, FuzzyImputationTest, lfproQC, missCompare, MSPrep, onlineBcp, promor, qmtools, robCompositions, sdcMicro, simPop, simputation
Reverse suggests: clusterMI, micemd

Linking:

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