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.
|Author||Matthias Templ, Andreas Alfons, Alexander Kowarik, Bernd Prantner|
|Date of publication||2016-10-17 12:41:12|
|Maintainer||Matthias Templ <email@example.com>|
|License||GPL (>= 2)|
aggr: Aggregations for missing/imputed values
alphablend: Alphablending for colors
barMiss: Barplot with information about missing/imputed values
bgmap: Backgound map
chorizonDL: C-horizon of the Kola data with missing values
colormapMiss: Colored map with information about missing/imputed values
colSequence: HCL and RGB color sequences
countInf: Count number of infinite or missing values
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
matrixplot: Matrix plot
mosaicMiss: Mosaic plot with information about missing/imputed values
pairsVIM: Scatterplot Matrices
parcoordMiss: Parallel coordinate plot with information about...
pbox: Parallel boxplots with information about missing/imputed...
prepare: Transformation and standardization
print.summary.aggr: Print method for objects of class summary.aggr
regressionImp: Regression Imputation
rugNA: Rug representation of missing/imputed values
SBS5242: Synthetic subset of the Austrian structural business...
scattJitt: Bivariate jitter plot
scattmatrixMiss: Scatterplot matrix with information about missing/imputed...
scattMiss: Scatterplot with information about missing/imputed values
sleep: Mammal sleep data
spineMiss: Spineplot with information about missing/imputed values
tao: Tropical Atmosphere Ocean (TAO) project data
testdata: Simulated data set for testing purpose
VIM-package: Visualization and Imputation of Missing Values
vmGUIenvir: Environment for the GUI for Visualization and Imputation of...