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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.

Functions (52)

SBS5242

Synthetic subset of the Austrian structural business statistics data

VIM-package

Visualization and Imputation of Missing Values

aggr

Aggregations for missing/imputed values

alphablend

Alphablending for colors

barMiss

Barplot with information about missing/imputed values

bcancer

Breast cancer Wisconsin data set

bgmap

Backgound map

brittleness

Brittleness index data set

chorizonDL

C-horizon of the Kola data with missing values

colSequence

HCL and RGB color sequences

colic

Colic horse data set

collisions

Subset of the collision data

colormapMiss

Colored map with information about missing/imputed values

countInf

Count number of infinite or missing values

diabetes

Indian Prime Diabetes Data

evaluation

Error performance measures

food

Food consumption

gapMiss

Missing value gap statistics

gowerD

Computes the extended Gower distance of two data sets

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

matchImpute

Fast matching/imputation based on categorical variable

matrixplot

Matrix plot

maxCat

Aggregation function for a factor variable

mosaicMiss

Mosaic plot with information about missing/imputed values

pairsVIM

Scatterplot Matrices

parcoordMiss

Parallel coordinate plot with information about missing/imputed values

pbox

Parallel boxplots with information about missing/imputed values

prepare

Transformation and standardization

pulplignin

Pulp lignin content

rangerImpute

Random Forest Imputation

regressionImp

Regression Imputation

rugNA

Rug representation of missing/imputed values

sampleCat

Random aggregation function for a factor variable

scattJitt

Bivariate jitter plot

scattMiss

Scatterplot with information about missing/imputed values

scattmatrixMiss

Scatterplot matrix with information about missing/imputed values

sleep

Mammal sleep data

spineMiss

Spineplot with information about missing/imputed values

tableMiss

create table with highlighted missings/imputations

tao

Tropical Atmosphere Ocean (TAO) project data

testdata

Simulated data set for testing purpose

toydataMiss

Simulated toy data set for examples

wine

Wine tasting and price

VIM

Visualization and Imputation of Missing Values

v6.1.0

GPL (>= 2)

Authors

Matthias Templ [aut, cre], Alexander Kowarik [aut] (<https://orcid.org/0000-0001-8598-4130>), Andreas Alfons [aut], Gregor de Cillia [aut], Bernd Prantner [ctb], Wolfgang Rannetbauer [aut]

Initial release

VIM

Functions (52)

VIM

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