Learn R Programming

⚠️There's a newer version (6.2.2) of this package.Take me there.

VIM (version 4.6.0)

Visualization and Imputation of Missing Values

Description

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.

Copy Link

Version

Install

install.packages('VIM')

Monthly Downloads

14,800

Version

4.6.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Matthias Templ

Last Published

October 17th, 2016

Functions in VIM (4.6.0)

aggr

Aggregations for missing/imputed values
countInf

Count number of infinite or missing values
barMiss

Barplot with information about missing/imputed values
alphablend

Alphablending for colors
bgmap

Backgound map
histMiss

Histogram with information about missing/imputed values
colSequence

HCL and RGB color sequences
growdotMiss

Growing dot map with information about missing/imputed values
colormapMiss

Colored map with information about missing/imputed values
hotdeck

Hot-Deck Imputation
kNN

k-Nearest Neighbour Imputation
irmi

Iterative robust model-based imputation (IRMI)
mapMiss

Map with information about missing/imputed values
mosaicMiss

Mosaic plot with information about missing/imputed values
initialise

Initialization of missing values
marginmatrix

Marginplot Matrix
pairsVIM

Scatterplot Matrices
marginplot

Scatterplot with additional information in the margins
kola.background

Background map for the Kola project data
matrixplot

Matrix plot
regressionImp

Regression Imputation
rugNA

Rug representation of missing/imputed values
pbox

Parallel boxplots with information about missing/imputed values
prepare

Transformation and standardization
parcoordMiss

Parallel coordinate plot with information about missing/imputed values
scattmatrixMiss

Scatterplot matrix with information about missing/imputed values
print.summary.aggr

Print method for objects of class summary.aggr
scattJitt

Bivariate jitter plot
SBS5242

Synthetic subset of the Austrian structural business statistics data
scattMiss

Scatterplot with information about missing/imputed values
vmGUIenvir

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

Simulated data set for testing purpose
VIM-package

Visualization and Imputation of Missing Values
spineMiss

Spineplot with information about missing/imputed values