VIM v6.0.0

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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.

Functions in VIM

Name Description
colic Colic horse data set
kola.background Background map for the Kola project data
food Food consumption
rangerImpute Random Forest Imputation
colormapMiss Colored map with information about missing/imputed values
gapMiss Missing value gap statistics
gowerD Computes the extended Gower distance of two data sets
mosaicMiss Mosaic plot with information about missing/imputed values
kNN k-Nearest Neighbour Imputation
evaluation Error performance measures
collisions Subset of the collision data
spineMiss Spineplot with information about missing/imputed values
diabetes Indian Prime Diabetes Data
scattMiss Scatterplot with information about missing/imputed values
growdotMiss Growing dot map with information about missing/imputed values
regressionImp Regression Imputation
marginplot Scatterplot with additional information in the margins
testdata Simulated data set for testing purpose
pairsVIM Scatterplot Matrices
irmi Iterative robust model-based imputation (IRMI)
tao Tropical Atmosphere Ocean (TAO) project data
initialise Initialization of missing values
VIM-package Visualization and Imputation of Missing Values
pbox Parallel boxplots with information about missing/imputed values
marginmatrix Marginplot Matrix
mapMiss Map with information about missing/imputed values
parcoordMiss Parallel coordinate plot with information about missing/imputed values
toydataMiss Simulated toy data set for examples
countInf Count number of infinite or missing values
matchImpute Fast matching/imputation based on categorical variable
prepare Transformation and standardization
maxCat Aggregation function for a factor variable
scattmatrixMiss Scatterplot matrix with information about missing/imputed values
scattJitt Bivariate jitter plot
matrixplot Matrix plot
histMiss Histogram with information about missing/imputed values
hotdeck Hot-Deck Imputation
rugNA Rug representation of missing/imputed values
sampleCat Random aggregation function for a factor variable
pulplignin Pulp lignin content
wine Wine tasting and price
sleep Mammal sleep data
barMiss Barplot with information about missing/imputed values
bgmap Backgound map
alphablend Alphablending for colors
aggr Aggregations for missing/imputed values
bcancer Breast cancer Wisconsin data set
brittleness Brittleness index data set
colSequence HCL and RGB color sequences
chorizonDL C-horizon of the Kola data with missing values
SBS5242 Synthetic subset of the Austrian structural business statistics data
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Vignettes of VIM

Name
VIM.Rmd
modelImp.Rmd
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Details

LazyData TRUE
ByteCompile TRUE
License GPL (>= 2)
URL https://github.com/statistikat/VIM
Repository CRAN
LinkingTo Rcpp
RoxygenNote 7.1.0
Encoding UTF-8
VignetteBuilder knitr
NeedsCompilation yes
Packaged 2020-05-08 11:48:49 UTC; matthias
Date/Publication 2020-05-08 13:30:02 UTC

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