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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.
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