toweranNA: 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)).

Version: 0.1.0
Depends: R (≥ 3.6.0), regtools (≥ 0.8.0), rmarkdown
Imports: FNN, pdist, stats
Published: 2023-03-15
DOI: 10.32614/CRAN.package.toweranNA
Author: Norm Matloff ORCID iD [aut, cre], Pete Mohanty ORCID iD [aut]
Maintainer: Norm Matloff <nsmatloff at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: MissingData
CRAN checks: toweranNA results


Reference manual: toweranNA.pdf


Package source: toweranNA_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): toweranNA_0.1.0.tgz, r-oldrel (arm64): toweranNA_0.1.0.tgz, r-release (x86_64): toweranNA_0.1.0.tgz, r-oldrel (x86_64): toweranNA_0.1.0.tgz

Reverse dependencies:

Reverse imports: qeML


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