predictset: Conformal Prediction and Uncertainty Quantification
Implements conformal prediction methods for constructing
prediction intervals (regression) and prediction sets (classification)
with finite-sample coverage guarantees. Methods include split conformal,
'CV+' and 'Jackknife+' (Barber et al. 2021) <doi:10.1214/20-AOS1965>,
'Conformalized Quantile Regression' (Romano et al. 2019)
<doi:10.48550/arXiv.1905.03222>, 'Adaptive Prediction Sets'
(Romano, Sesia, Candes 2020) <doi:10.48550/arXiv.2006.02544>,
'Regularized Adaptive Prediction Sets' (Angelopoulos et al. 2021)
<doi:10.48550/arXiv.2009.14193>, Mondrian conformal prediction for
group-conditional coverage (Vovk et al. 2005), weighted conformal
prediction for covariate shift (Tibshirani et al. 2019), and adaptive
conformal inference for sequential prediction (Gibbs and Candes 2021).
All methods are distribution-free and provide calibrated uncertainty
quantification without parametric assumptions. Works with any model that can
produce predictions from new data, including 'lm', 'glm', 'ranger',
'xgboost', and custom user-defined models.
| Version: |
0.3.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
cli (≥ 3.6.0), grDevices, graphics, stats |
| Suggests: |
testthat (≥ 3.0.0), ranger, ggplot2, knitr, rmarkdown, parsnip (≥ 1.0.0), probably, rsample, workflows |
| Published: |
2026-03-19 |
| DOI: |
10.32614/CRAN.package.predictset (may not be active yet) |
| Author: |
Charles Coverdale [aut, cre, cph] |
| Maintainer: |
Charles Coverdale <charlesfcoverdale at gmail.com> |
| BugReports: |
https://github.com/charlescoverdale/predictset/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/charlescoverdale/predictset |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
predictset citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
predictset results |
Documentation:
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