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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