VIM: Visualization and Imputation of Missing Values

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>).

Package details

AuthorMatthias Templ [aut, cre] (<https://orcid.org/0000-0002-8638-5276>), Alexander Kowarik [aut] (<https://orcid.org/0000-0001-8598-4130>), Andreas Alfons [aut], Bernd Prantner [ctb]
MaintainerMatthias Templ <matthias.templ@gmail.com>
LicenseGPL (>= 2)
Version5.1.1
URL https://github.com/statistikat/VIM
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("VIM")

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VIM documentation built on March 13, 2020, 1:34 a.m.