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 [aut, cre], Pete Mohanty [aut]
Maintainer:	Norm Matloff <nsmatloff at ucdavis.edu>
BugReports:	https://github.com/matloff/toweranNA/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/matloff/toweranNA
NeedsCompilation:	no
In views:	MissingData
CRAN checks:	toweranNA results

Documentation:

Reference manual:

toweranNA.pdf

Downloads:

Package source:	toweranNA_0.1.0.tar.gz
Windows binaries:	r-devel: toweranNA_0.1.0.zip, r-release: toweranNA_0.1.0.zip, r-oldrel: toweranNA_0.1.0.zip
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

Linking:

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