ConformalSmallest: Efficient Tuning-Free Conformal Prediction

An implementation of efficiency first conformal prediction (EFCP) and validity first conformal prediction (VFCP) that demonstrates both validity (coverage guarantee) and efficiency (width guarantee). To learn how to use it, check the vignettes for a quick tutorial. The package is based on the work by Yang Y., Kuchibhotla A.,(2021) <doi:10.48550/arXiv.2104.13871>.

Version: 1.0
Depends: R (≥ 3.5.0)
Imports: glmnet, mvtnorm, stats, MASS, quantregForest
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, ggplot2, repr
Published: 2021-08-09
DOI: 10.32614/CRAN.package.ConformalSmallest
Author: Yachong Yang [aut, cre]
Maintainer: Yachong Yang <yachong at wharton.upenn.edu>
License: GPL (≥ 3)
URL: https://github.com/Elsa-Yang98/ConformalSmallest
NeedsCompilation: no
Materials: README
CRAN checks: ConformalSmallest results

Documentation:

Reference manual: ConformalSmallest.pdf
Vignettes: Example-tuning_free_CQR
Example-tuning-free_ridge_regression

Downloads:

Package source: ConformalSmallest_1.0.tar.gz
Windows binaries: r-devel: ConformalSmallest_1.0.zip, r-release: ConformalSmallest_1.0.zip, r-oldrel: ConformalSmallest_1.0.zip
macOS binaries: r-release (arm64): ConformalSmallest_1.0.tgz, r-oldrel (arm64): ConformalSmallest_1.0.tgz, r-release (x86_64): ConformalSmallest_1.0.tgz, r-oldrel (x86_64): ConformalSmallest_1.0.tgz

Linking:

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