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Package: VIM
Version: 6.1.0
Title: Visualization and Imputation of Missing Values
Authors@R: c(
person("Matthias", "Templ", email = "matthias.templ@gmail.com", role = c("aut","cre")),
person("Alexander", "Kowarik", email = "alexander.kowarik@statistik.gv.at", role = c("aut"), comment=c(ORCID="0000-0001-8598-4130")),
person("Andreas", "Alfons", role = c("aut")),
person("Gregor", "de Cillia", email = "gregor.decillia@statistik.gv.at", role = c("aut")),
person("Bernd", "Prantner", role = c("ctb")),
person("Wolfgang", "Rannetbauer", role = c("aut")))
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)
Suggests: dplyr, testthat (>= 2.1.0), knitr, rmarkdown, reactable
Description: 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.
LazyData: TRUE
ByteCompile: TRUE
License: GPL (>= 2)
URL: https://github.com/statistikat/VIM
Repository: CRAN
LinkingTo: Rcpp
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-19 06:04:33 UTC; kowa
Author: Matthias Templ [aut, cre],
Alexander Kowarik [aut] (<https://orcid.org/0000-0001-8598-4130>),
Andreas Alfons [aut],
Gregor de Cillia [aut],
Bernd Prantner [ctb],
Wolfgang Rannetbauer [aut]
Maintainer: Matthias Templ <matthias.templ@gmail.com>
Date/Publication: 2021-01-19 17:00:13 UTC
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