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predictset 0.3.0

Documentation

• Documented Jackknife+ and CV+ theoretical coverage guarantee (1-2alpha) per Barber et al. (2021)
• Documented ACI asymptotic (not finite-sample) coverage guarantee per Gibbs and Candes (2021)
• Documented CQR dependence on quantile model quality
• Documented deterministic vs randomized APS variants
• Added coverage guarantee footnotes to README and vignette method tables

Internal

• Added graphics and grDevices to DESCRIPTION Imports
• Added missing test dependencies to Suggests

predictset 0.2.0

New features

• conformal_mondrian() and conformal_mondrian_class() for group-conditional (Mondrian) conformal prediction
• conformal_weighted() for weighted conformal prediction under covariate shift
• conformal_aci() for adaptive conformal inference (sequential prediction)
• conformal_pvalue() for conformal p-values
• conformal_compare() for benchmarking multiple methods side-by-side
• coverage_by_group() and coverage_by_bin() for conditional coverage diagnostics
• Progress bars via verbose = TRUE for conformal_jackknife() and conformal_cv()

Improvements

• NA/NaN/Inf input validation with informative error messages
• Column dimension checks between training and test data
• Probability matrix column validation for classification methods
• Graceful handling of unseen factor levels in APS/RAPS/LAC scoring
• Negative scale model prediction warnings for normalized conformal

predictset 0.1.0

• Initial release with split conformal, CV+, Jackknife+, CQR (regression) and split, APS, RAPS, LAC (classification)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.