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').


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install.packages("GenForImp")

1.0 by Alessandro Barbiero, 7 years ago


Browse source code at https://github.com/cran/GenForImp


Authors: Nadia Solaro , Alessandro Barbiero , Giancarlo Manzi , Pier Alda Ferrari


Documentation:   PDF Manual  


Task views: Missing Data


GPL-3 license


Depends on mvtnorm, sn


See at CRAN