scR: Empirical Sample Complexity Bounds

Provides tools for estimating empirical sample complexity bounds for supervised learning tasks. The package supports simulation-based estimates of generalization curves, parametric extrapolation of empirical sample complexity bounds, theoretical bounds based on Vapnik-Chervonenkis dimension, and optional monotone Gaussian process extrapolation for users who install the external 'cmdstanr' workflow. For more details, see Carter and Choi (2024) <doi:10.31219/osf.io/evrcj>.

Version:	0.7.0
Depends:	R (≥ 4.1.0)
Imports:	dplyr, furrr, future, ggplot2, Matrix, minpack.lm, parallel, parallelly, pbapply, plotly, progressr, stats, tidyr
Suggests:	cmdstanr, posterior, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-06-23
DOI:	10.32614/CRAN.package.scR
Author:	Perry Carter [aut, cre], Dahyun Choi [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
Additional_repositories:	https://stan-dev.r-universe.dev
Materials:	README, NEWS
CRAN checks:	scR results

Documentation:

Reference manual:

scR.html , scR.pdf

Downloads:

Package source:	scR_0.7.0.tar.gz
Windows binaries:	r-devel: scR_0.7.0.zip, r-release: scR_0.7.0.zip, r-oldrel: scR_0.7.0.zip
macOS binaries:	r-release (arm64): scR_0.7.0.tgz, r-oldrel (arm64): scR_0.7.0.tgz, r-release (x86_64): scR_0.7.0.tgz, r-oldrel (x86_64): scR_0.7.0.tgz
Old sources:	scR archive

Linking:

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