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VIM (version 5.1.1)

Visualization and Imputation of Missing Values

Description

Methods for the visualization of missing and/or imputed values are provided, 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. Fast imputation methods such as k-nearest neighbor imputation () and (multiple) EM-based imputation using robust methods are provided ().

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Version

Install

install.packages('VIM')

Monthly Downloads

16,871

Version

5.1.1

License

GPL (>= 2)

Issues

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Maintainer

Matthias Templ

Last Published

March 10th, 2020

Functions in VIM (5.1.1)

chorizonDL

C-horizon of the Kola data with missing values
brittleness

Brittleness index data set
alphablend

Alphablending for colors
SBS5242

Synthetic subset of the Austrian structural business statistics data
bcancer

Breast cancer Wisconsin data set
VIM-package

Visualization and Imputation of Missing Values
aggr

Aggregations for missing/imputed values
gowerD

Computes the extended Gower distance of two data sets
bgmap

Backgound map
collisions

Subset of the collision data
barMiss

Barplot with information about missing/imputed values
diabetes

Indian Prime Diabetes Data
colormapMiss

Colored map with information about missing/imputed values
food

Food consumption
colSequence

HCL and RGB color sequences
countInf

Count number of infinite or missing values
colic

Colic horse data set
marginmatrix

Marginplot Matrix
gapMiss

Missing value gap statistics
growdotMiss

Growing dot map with information about missing/imputed values
marginplot

Scatterplot with additional information in the margins
mapMiss

Map with information about missing/imputed values
irmi

Iterative robust model-based imputation (IRMI)
evaluation

Error performance measures
histMiss

Histogram with information about missing/imputed values
kNN

k-Nearest Neighbour Imputation
hotdeck

Hot-Deck Imputation
initialise

Initialization of missing values
prepare

Transformation and standardization
tao

Tropical Atmosphere Ocean (TAO) project data
parcoordMiss

Parallel coordinate plot with information about missing/imputed values
pulplignin

Pulp lignin content
maxCat

Aggregation function for a factor variable
mosaicMiss

Mosaic plot with information about missing/imputed values
sampleCat

Random aggregation function for a factor variable
pairsVIM

Scatterplot Matrices
pbox

Parallel boxplots with information about missing/imputed values
matrixplot

Matrix plot
matchImpute

Fast matching/imputation based on categorical variable
regressionImp

Regression Imputation
kola.background

Background map for the Kola project data
scattJitt

Bivariate jitter plot
toydataMiss

Simulated toy data set for examples
sleep

Mammal sleep data
wine

Wine tasting and price
testdata

Simulated data set for testing purpose
scattMiss

Scatterplot with information about missing/imputed values
vmGUIenvir

Environment for the GUI for Visualization and Imputation of Missing Values
rugNA

Rug representation of missing/imputed values
spineMiss

Spineplot with information about missing/imputed values
scattmatrixMiss

Scatterplot matrix with information about missing/imputed values