Statistics, Department of
The R Journal
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Date of this Version
7-2018
Document Type
Article
Citation
The R Journal (July 2018) 10(1); Editor: John Verzani
Abstract
Data analysis, common to all empirical sciences, often requires complete data sets. Unfortunately, real world data collection will usually result in data values not being observed. We present a package for robust multiple imputation (the ImputeRobust package) that allows the use of generalized additive models for location, scale, and shape in the context of chained equations. The paper describes the basics of the imputation technique which builds on a semi-parametric regression model (GAMLSS) and the algorithms and functions provided with the corresponding package. Furthermore, some illustrative examples are provided.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2018, The R Foundation. Open access material. License: CC BY 4.0 International