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:
6.2.6
Imports:
car, grDevices,
robustbase, stats,
sp,
vcd,
nnet,
e1071, methods,
Rcpp, utils, graphics,
laeken,
ranger,
MASS,
xgboost,
data.table (≥ 1.9.4)
Suggests:
dplyr,
tinytest,
knitr,
mgcv,
rmarkdown,
reactable,
covr,
withr,
pdist,
enetLTS,
robmixglm,
stringr
Published:
2025年09月18日
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>
NeedsCompilation:
yes
Documentation:
Downloads:
Reverse dependencies:
Reverse imports:
destiny,
fastml,
FuzzyImputationTest,
lfproQC,
MAICtools,
MIGEE,
missCompare,
MSPrep,
onlineBcp,
promor,
qmtools,
robCompositions,
sdcMicro,
simPop,
simputation
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=VIM
to link to this page.