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scR: Estimate Vapnik-Chervonenkis Dimension and Sample Complexity

We provide a suite of tools for estimating the sample complexity of a chosen model through theoretical bounds and simulation. The package incorporates methods for estimating the Vapnik-Chervonenkis dimension (VCD) of a chosen algorithm, which can be used to estimate its sample complexity. Alternatively, we provide simulation methods to estimate sample complexity directly. For more details, see Carter, P & Choi, D (2024). "Learning from Noise: Applying Sample Complexity for Political Science Research" <doi:10.31219/osf.io/evrcj>.

Version: 0.4.0
Depends: R (≥ 2.10)
Imports: parallel, pbapply, caret, dplyr, tidyr, ggplot2, plotly
Suggests: rmarkdown
Published: 2024-12-23
DOI: 10.32614/CRAN.package.scR
Author: Perry Carter ORCID iD [aut, cre], Dahyun Choi ORCID iD [aut]
Maintainer: Perry Carter <pjc504 at nyu.edu>
BugReports: https://github.com/pjesscarter/scR/issues
License: MIT + file LICENSE
URL: https://github.com/pjesscarter/scR
NeedsCompilation: no
Materials: README
CRAN checks: scR results

Documentation:

Reference manual: scR.pdf

Downloads:

Package source: scR_0.4.0.tar.gz
Windows binaries: r-devel: scR_0.4.0.zip, r-release: scR_0.4.0.zip, r-oldrel: scR_0.4.0.zip
macOS binaries: r-release (arm64): scR_0.4.0.tgz, r-oldrel (arm64): scR_0.4.0.tgz, r-release (x86_64): scR_0.4.0.tgz, r-oldrel (x86_64): scR_0.4.0.tgz
Old sources: scR archive

Linking:

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