Package: predictset Title: Conformal Prediction and Uncertainty Quantification Version: 0.3.2 Authors@R: person("Charles", "Coverdale", email = "charlesfcoverdale@gmail.com", role = c("aut", "cre", "cph")) Description: 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) , 'Conformalized Quantile Regression' (Romano et al. 2019) , 'Adaptive Prediction Sets' (Romano, Sesia, Candes 2020) , 'Regularized Adaptive Prediction Sets' (Angelopoulos et al. 2021) , Mondrian conformal prediction for group-conditional coverage (Vovk, Gammerman, and Shafer 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. License: MIT + file LICENSE Encoding: UTF-8 Language: en-US URL: https://charlescoverdale.github.io/predictset/, https://github.com/charlescoverdale/predictset BugReports: https://github.com/charlescoverdale/predictset/issues Roxygen: list(markdown = TRUE) RoxygenNote: 7.3.3 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 VignetteBuilder: knitr Config/testthat/edition: 3 Repository: https://charlescoverdale.r-universe.dev Date/Publication: 2026-05-30 15:06:31 UTC RemoteUrl: https://github.com/charlescoverdale/predictset RemoteRef: HEAD RemoteSha: 350b68bf5f8468a491aad60c414a1b300dad986e NeedsCompilation: no Packaged: 2026-07-04 09:01:13 UTC; root Author: Charles Coverdale [aut, cre, cph] Maintainer: Charles Coverdale