toydataMiss

<p>A 2-dimensional data set with additional information.</p>

datasets

Methods for the visualization of missing and/or imputed values
are provided, 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 (<doi:10.1007/s11634-011-0102-y>). A graphical user
interface available in the separate package VIMGUI allows an easy handling of
the implemented plot methods.
Fast imputation methods such as k-nearest neighbor imputation (<doi:10.18637/jss.v074.i07>) and
(multiple) EM-based imputation using robust methods are provided (<doi:10.1016/j.csda.2011.04.012>).

Matthias Templ

Visualization and Imputation of Missing Values

Alexander Kowarik

Andreas Alfons

Bernd Prantner

toydataMiss function

<p>data frame with 100 observations and 12 variables. The first two 
variables represent the fully observed data.</p>

toydataMiss: Simulated toy data set for examples

Description

Arguments

Format

Examples