Empirical Sample Complexity Bounds R package scR version 0.7.0 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>. Software 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) Perry Carter <pjc504@nyu.edu> Comprehensive R Archive Network (CRAN) Perry Carter [aut, cre] (ORCID: <https://orcid.org/0000-0002-4684-6533>), Dahyun Choi [aut] (ORCID: <https://orcid.org/0000-0002-2628-1467>) MIT + file LICENSE (https://CRAN.R-project.org/package=scR/LICENSE) 2026-06-23 application/tgz https://CRAN.R-project.org/package=scR doi:10.32614/CRAN.package.scR