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PLORN: Prediction with Less Overfitting and Robust to Noise

A method for the quantitative prediction with much predictors. This package provides functions to construct the quantitative prediction model with less overfitting and robust to noise.

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: ggplot2, kernlab
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-03-21
DOI: 10.32614/CRAN.package.PLORN
Author: Takahiko Koizumi, Kenta Suzuki, Yasunori Ichihashi
Maintainer: Takahiko Koizumi <takahiko.koizumi at riken.jp>
License: MIT + file LICENSE
URL: https://github.com/takakoizumi/PLORN
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: PLORN results

Documentation:

Reference manual: PLORN.pdf
Vignettes: PLORN

Downloads:

Package source: PLORN_0.1.1.tar.gz
Windows binaries: r-devel: PLORN_0.1.1.zip, r-release: PLORN_0.1.1.zip, r-oldrel: PLORN_0.1.1.zip
macOS binaries: r-release (arm64): PLORN_0.1.1.tgz, r-oldrel (arm64): PLORN_0.1.1.tgz, r-release (x86_64): PLORN_0.1.1.tgz, r-oldrel (x86_64): PLORN_0.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PLORN to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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