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Cited by 659

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Imputation with the R Package VIM

Open access
Kowarik, Alexander, Templ, Matthias·2016·Journal of Statistical Software
DOI 10.18637/jss.v074.i07
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Abstract

The package VIM (Templ, Alfons, Kowarik, and Prantner 2016) is developed to explore and analyze the structure of missing values in data using visualization methods, to impute these missing values with the built-in imputation methods and to verify the imputation process using visualization tools, as well as to produce high-quality graphics for publications. This article focuses on the different imputation techniques available in the package. Four different imputation methods are currently implemented in VIM, namely hot-deck imputation, k-nearest neighbor imputation, regression imputation and iterative robust model-based imputation (Templ, Kowarik, and Filzmoser 2011). All of these methods are implemented in a flexible manner with many options for customization. Furthermore in this article practical examples are provided to highlight the use of the implemented methods on real-world applications. In addition, the graphical user interface of VIM has been re-implemented from scratch resulting in the package VIMGUI (Schopfhauser, Templ, Alfons, Kowarik, and Prantner 2016) to enable users without extensive R skills to access these imputation and visualization methods.

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Metadata

Authors
Kowarik, A., & Templ, M.
Venue
Journal of Statistical Software
Publisher
Foundation for Open Access Statistic
Published
2016
Volume
74
Issue
7
ISSN
1548-7660 (ISSN-L)
DOI
10.18637/jss.v074.i07
OpenAlex
W2534722177
Cited by
659
References
24
FWCI
30.51
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Imputation with the R Package VIM. https://app.cochat.ai/papers/10.18637/jss.v074.i07
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Kowarik, A., & Templ, M. (2016). Imputation with the R Package VIM. Journal of Statistical Software. https://doi.org/10.18637/jss.v074.i07

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