GenForImp: The Forward Imputation: A Sequential Distance-Based Approach for Imputing Missing Data

Two methods based on the Forward Imputation approach are implemented for the imputation of quantitative missing data. One method alternates Nearest Neighbour Imputation and Principal Component Analysis (function 'ForImp.PCA'), the other uses Nearest Neighbour Imputation with the Mahalanobis distance (function 'ForImp.Mahala').

Version: 1.0
Depends: mvtnorm, sn
Published: 2015-02-27
Author: Nadia Solaro, Alessandro Barbiero, Giancarlo Manzi, Pier Alda Ferrari
Maintainer: Alessandro Barbiero <alessandro.barbiero at unimi.it>
License: GPL-3
NeedsCompilation: no
In views: MissingData
CRAN checks: GenForImp results

Downloads:

Reference manual: GenForImp.pdf
Package source: GenForImp_1.0.tar.gz
Windows binaries: r-devel: GenForImp_1.0.zip, r-devel-gcc8: GenForImp_1.0.zip, r-release: GenForImp_1.0.zip, r-oldrel: GenForImp_1.0.zip
OS X binaries: r-release: GenForImp_1.0.tgz, r-oldrel: GenForImp_1.0.tgz

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