Visualization and Imputation of Missing Values


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Documentation for package ‘VIM’ version 5.1.1

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A B C D E F G H I K L M N P R S T V W

VIM-package Visualization and Imputation of Missing Values

-- A --

aggr Aggregations for missing/imputed values
aggr.data.frame Aggregations for missing/imputed values
aggr.default Aggregations for missing/imputed values
aggr.survey.design Aggregations for missing/imputed values
aggr_work Aggregations for missing/imputed values
alphablend Alphablending for colors

-- B --

barMiss Barplot with information about missing/imputed values
barMiss.data.frame Barplot with information about missing/imputed values
barMiss.default Barplot with information about missing/imputed values
barMiss.survey.design Barplot with information about missing/imputed values
bcancer Breast cancer Wisconsin data set
bgmap Backgound map
brittleness Brittleness index data set
bubbleMiss Growing dot map with information about missing/imputed values

-- C --

chorizonDL C-horizon of the Kola data with missing values
colic Colic horse data set
collisions Subset of the collision data
colormapMiss Colored map with information about missing/imputed values
colormapMiss.data.frame Colored map with information about missing/imputed values
colormapMiss.default Colored map with information about missing/imputed values
colormapMiss.survey.design Colored map with information about missing/imputed values
colormapMissLegend Colored map with information about missing/imputed values
colSequence HCL and RGB color sequences
colSequenceHCL HCL and RGB color sequences
colSequenceRGB HCL and RGB color sequences
countInf Count number of infinite or missing values
countNA Count number of infinite or missing values

-- D --

diabetes Indian Prime Diabetes Data

-- E --

evaluation Error performance measures
existsVm Environment for the GUI for Visualization and Imputation of Missing Values

-- F --

food Food consumption

-- G --

gapMiss Missing value gap statistics
getVm Environment for the GUI for Visualization and Imputation of Missing Values
gowerD Computes the extended Gower distance of two data sets
growdotMiss Growing dot map with information about missing/imputed values
growdotMiss.data.frame Growing dot map with information about missing/imputed values
growdotMiss.default Growing dot map with information about missing/imputed values
growdotMiss.survey.design Growing dot map with information about missing/imputed values

-- H --

histMiss Histogram with information about missing/imputed values
histMiss.data.frame Histogram with information about missing/imputed values
histMiss.default Histogram with information about missing/imputed values
histMiss.survey.design Histogram with information about missing/imputed values
hotdeck Hot-Deck Imputation
hotdeck.data.frame Hot-Deck Imputation
hotdeck.default Hot-Deck Imputation
hotdeck.survey.design Hot-Deck Imputation

-- I --

iimagMiss Matrix plot
initialise Initialization of missing values
irmi Iterative robust model-based imputation (IRMI)
irmi.data.frame Iterative robust model-based imputation (IRMI)
irmi.default Iterative robust model-based imputation (IRMI)
irmi.survey.design Iterative robust model-based imputation (IRMI)

-- K --

kNN k-Nearest Neighbour Imputation
kNN.data.frame k-Nearest Neighbour Imputation
kNN.data.table k-Nearest Neighbour Imputation
kNN.default k-Nearest Neighbour Imputation
kNN.survey.design k-Nearest Neighbour Imputation
kola.background Background map for the Kola project data

-- L --

lr Error performance measures

-- M --

mape Error performance measures
mapMiss Map with information about missing/imputed values
mapMiss.data.frame Map with information about missing/imputed values
mapMiss.default Map with information about missing/imputed values
mapMiss.survey.design Map with information about missing/imputed values
marginmatrix Marginplot Matrix
marginmatrix.data.frame Marginplot Matrix
marginmatrix.default Marginplot Matrix
marginmatrix.survey.design Marginplot Matrix
marginplot Scatterplot with additional information in the margins
matchImpute Fast matching/imputation based on categorical variable
matchImpute.data.frame Fast matching/imputation based on categorical variable
matchImpute.data.table Fast matching/imputation based on categorical variable
matchImpute.default Fast matching/imputation based on categorical variable
matchImpute.survey.design Fast matching/imputation based on categorical variable
matrixplot Matrix plot
matrixplot.data.frame Matrix plot
matrixplot.default Matrix plot
matrixplot.survey.design Matrix plot
maxCat Aggregation function for a factor variable
mosaicMiss Mosaic plot with information about missing/imputed values
mosaicMiss.data.frame Mosaic plot with information about missing/imputed values
mosaicMiss.default Mosaic plot with information about missing/imputed values
mosaicMiss.survey.design Mosaic plot with information about missing/imputed values
msecor Error performance measures
msecov Error performance measures

-- N --

nrmse Error performance measures

-- P --

pairsVIM Scatterplot Matrices
parcoordMiss Parallel coordinate plot with information about missing/imputed values
parcoordMiss.data.frame Parallel coordinate plot with information about missing/imputed values
parcoordMiss.default Parallel coordinate plot with information about missing/imputed values
parcoordMiss.survey.design Parallel coordinate plot with information about missing/imputed values
pbox Parallel boxplots with information about missing/imputed values
pbox.data.frame Parallel boxplots with information about missing/imputed values
pbox.default Parallel boxplots with information about missing/imputed values
pbox.survey.design Parallel boxplots with information about missing/imputed values
pfc Error performance measures
plot.aggr Aggregations for missing/imputed values
prepare Transformation and standardization
prepare.data.frame Transformation and standardization
prepare.default Transformation and standardization
prepare.survey.design Transformation and standardization
print.aggr Aggregations for missing/imputed values
print.summary.aggr Aggregations for missing/imputed values
pulplignin Pulp lignin content
putVm Environment for the GUI for Visualization and Imputation of Missing Values

-- R --

regressionImp Regression Imputation
regressionImp.data.frame Regression Imputation
regressionImp.default Regression Imputation
regressionImp.survey.design Regression Imputation
rmVm Environment for the GUI for Visualization and Imputation of Missing Values
rugNA Rug representation of missing/imputed values

-- S --

sampleCat Random aggregation function for a factor variable
SBS5242 Synthetic subset of the Austrian structural business statistics data
scattJitt Bivariate jitter plot
scattmatrixMiss Scatterplot matrix with information about missing/imputed values
scattmatrixMiss.data.frame Scatterplot matrix with information about missing/imputed values
scattmatrixMiss.default Scatterplot matrix with information about missing/imputed values
scattmatrixMiss.survey.design Scatterplot matrix with information about missing/imputed values
scattMiss Scatterplot with information about missing/imputed values
sleep Mammal sleep data
smape Error performance measures
spineMiss Spineplot with information about missing/imputed values
summary.aggr Aggregations for missing/imputed values

-- T --

tao Tropical Atmosphere Ocean (TAO) project data
testdata Simulated data set for testing purpose
TKRmatrixplot Matrix plot
toydataMiss Simulated toy data set for examples

-- V --

VIM Visualization and Imputation of Missing Values
vmGUIenvir Environment for the GUI for Visualization and Imputation of Missing Values

-- W --

wine Wine tasting and price