Package index • VIM

Imputation methods Functions to impute missing data
`hotdeck()`	Hot-Deck Imputation
`impPCA()`	Iterative EM PCA imputation
`irmi()`	Iterative robust model-based imputation (IRMI)
`kNN()`	k-Nearest Neighbour Imputation
`matchImpute()`	Fast matching/imputation based on categorical variable
`medianSamp()`	Aggregation function for a ordinal variable
`rangerImpute()`	Random Forest Imputation
`regressionImp()`	Regression Imputation
`sampleCat()`	Random aggregation function for a factor variable
`xgboostImpute()`	Xgboost Imputation
`initialise()`	Initialization of missing values
`maxCat()`	Aggregation function for a factor variable
Plotting functions Functions to visualize missing and imputed values. See the visualization vignette for an overview.
`aggr()` `plot(<aggr>)` `print(<aggr>)` `summary(<aggr>)` `print(<summary.aggr>)`	Aggregations for missing/imputed values
`barMiss()`	Barplot with information about missing/imputed values
`histMiss()`	Histogram 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 missing/imputed values
`pbox()`	Parallel boxplots with information about missing/imputed values
`scattJitt()`	Bivariate jitter plot
`scattMiss()`	Scatterplot with information about missing/imputed values
`scattmatrixMiss()`	Scatterplot matrix with information about missing/imputed values
`spineMiss()`	Spineplot with information about missing/imputed values
`colSequence()` `colSequenceRGB()` `colSequenceHCL()`	HCL and RGB color sequences
`rugNA()`	Rug representation of missing/imputed values
`alphablend()`	Alphablending for colors
Maps
`colormapMiss()` `colormapMissLegend()`	Colored map with information about missing/imputed values
`mapMiss()`	Map with information about missing/imputed values
`bgmap()`	Backgound map
`growdotMiss()`	Growing dot map with information about missing/imputed values
Datasets Datasets to showcase several functionalities of VIM.
`Animals_na`	Animals_na
`SBS5242`	Synthetic subset of the Austrian structural business statistics data
`bcancer`	Breast cancer Wisconsin data set
`brittleness`	Brittleness index data set
`chorizonDL`	C-horizon of the Kola data with missing values
`colic`	Colic horse data set
`collisions`	Subset of the collision data
`diabetes`	Indian Prime Diabetes Data
`food`	Food consumption
`kola.background`	Background map for the Kola project data
`pulplignin`	Pulp lignin content
`sleep`	Mammal sleep data
`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
Other
`VIM-package` `VIM`	Visualization and Imputation of Missing Values
`countInf()`	Count number of infinite or missing values
`evaluation()` `nrmse()` `pfc()` `msecov()` `msecor()`	Error performance measures
`gowerD()`	Computes the extended Gower distance of two data sets
`prepare()`	Transformation and standardization
`gapMiss()`	Missing value gap statistics
`tableMiss()`	create table with highlighted missings/imputations

Reference

Imputation methods

Plotting functions

Maps

Datasets

Other