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.

Install the latest version of this package by entering the following in R:
AuthorMatthias Templ, Andreas Alfons, Alexander Kowarik, Bernd Prantner
Date of publication2017-04-11 13:38:48 UTC
MaintainerMatthias Templ <>
LicenseGPL (>= 2)

View on CRAN

Man pages

aggr: Aggregations for missing/imputed values

alphablend: Alphablending for colors

barMiss: Barplot with information about missing/imputed values

bgmap: Backgound map

chorizonDL: C-horizon of the Kola data with missing values

colormapMiss: Colored map with information about missing/imputed values

colSequence: HCL and RGB color sequences

countInf: Count number of infinite or missing values

growdotMiss: Growing dot map with information about missing/imputed values

histMiss: Histogram with information about missing/imputed values

hotdeck: Hot-Deck Imputation

initialise: Initialization of missing values

irmi: Iterative robust model-based imputation (IRMI)

kNN: k-Nearest Neighbour Imputation

kola.background: Background map for the Kola project data

mapMiss: Map with information about missing/imputed values

marginmatrix: Marginplot Matrix

marginplot: Scatterplot with additional information in the margins

matrixplot: Matrix plot

mosaicMiss: Mosaic plot with information about missing/imputed values

pairsVIM: Scatterplot Matrices

parcoordMiss: Parallel coordinate plot with information about...

pbox: Parallel boxplots with information about missing/imputed...

prepare: Transformation and standardization

print.summary.aggr: Print method for objects of class summary.aggr

regressionImp: Regression Imputation

rugNA: Rug representation of missing/imputed values

SBS5242: Synthetic subset of the Austrian structural business...

scattJitt: Bivariate jitter plot

scattmatrixMiss: Scatterplot matrix with information about missing/imputed...

scattMiss: Scatterplot with information about missing/imputed values

sleep: Mammal sleep data

spineMiss: Spineplot with information about missing/imputed values

tao: Tropical Atmosphere Ocean (TAO) project data

testdata: Simulated data set for testing purpose

VIM-package: Visualization and Imputation of Missing Values

vmGUIenvir: Environment for the GUI for Visualization and Imputation of...


aggr Man page
alphablend Man page
barMiss Man page
bgmap Man page
bubbleMiss Man page
chorizonDL Man page
colormapMiss Man page
colormapMissLegend Man page
colSequence Man page
colSequenceHCL Man page
colSequenceRGB Man page
countInf Man page
countNA Man page
existsVm Man page
getVm Man page
gowerD Man page
growdotMiss Man page
histMiss Man page
hotdeck Man page
iimagMiss Man page
initialise Man page
irmi Man page
kNN Man page
kola.background Man page
mapMiss Man page
marginmatrix Man page
marginplot Man page
matrixplot Man page
maxCat Man page
mosaicMiss Man page
pairsVIM Man page
parcoordMiss Man page
pbox Man page
plot.aggr Man page
prepare Man page
print.aggr Man page
print.summary.aggr Man page
putVm Man page
regressionImp Man page
rmVm Man page
rugNA Man page
sampleCat Man page
SBS5242 Man page
scattJitt Man page
scattmatrixMiss Man page
scattMiss Man page
sleep Man page
spineMiss Man page
summary.aggr Man page
tao Man page
testdata Man page
TKRmatrixplot Man page
VIM Man page
VIM-package Man page
vmGUIenvir Man page
which.minN Man page

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