A Method for Handling Missing Values in Prediction Applications

Non-imputational method for handling missing values in a prediction context, meaning that not only are there missing values in the training dataset, but also some values may be missing in future cases to be predicted. Based on the notion of regression averaging (Matloff (2017, ISBN: 9781498710916)).


Reference manual

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install.packages("toweranNA")

0.1.0 by Norm Matloff, 4 years ago


https://github.com/matloff/toweranNA


Report a bug at https://github.com/matloff/toweranNA/issues


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


Authors: Norm Matloff [aut, cre] , Pete Mohanty [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports FNN, pdist, stats

Depends on regtools, rmarkdown


Imported by mvPred, qeML.


See at CRAN