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Title: Imputation with the R Package VIM
Authors : Kowarik, Alexander
Templ, Matthias
Published in : Journal of Statistical Software
Volume(Issue) : 74
Issue : 7
Pages : 1
Pages to: 16
Publisher / Ed. Institution : UCLA, Dept. of Statistics
Issue Date: 2016
License (according to publishing contract) : CC BY 2.0: Namensnennung 2.0 Generic
Type of review: Peer review (Publication)
Language : English
Subject (DDC) : 005: Computer programming, programs and data
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.
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Publication type: Article in scientific Journal
DOI : 10.18637/jss.v074.i07
ISSN: 1548-7660
Appears in Collections:Publikationen School of Engineering

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