VIM: Visualization and Imputation of Missing Values

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: 4.6.0
Depends: R (≥ 3.1.0), colorspace, grid, data.table (≥ 1.9.4)
Imports: car, grDevices, robustbase, stats, sp, vcd, MASS, nnet, e1071, methods, Rcpp, utils, graphics, laeken
LinkingTo: Rcpp
Suggests: dplyr
Published: 2016-10-17
Author: Matthias Templ, Andreas Alfons, Alexander Kowarik, Bernd Prantner
Maintainer: Matthias Templ <matthias.templ at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: VIM citation info
Materials: README NEWS
In views: Multivariate, OfficialStatistics, SocialSciences
CRAN checks: VIM results


Reference manual: VIM.pdf
Package source: VIM_4.6.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: VIM_4.6.0.tgz, r-oldrel: VIM_4.6.0.tgz
Old sources: VIM archive

Reverse dependencies:

Reverse depends: VIMGUI
Reverse imports: covmat, robCompositions, simPop


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