predictset

• The model argument was discarded whenever it was a formula or a fitted model object, and a plain lm(y ~ .) was fitted in its place. model = y ~ a silently fitted every column of x; lm(y ~ poly(v1, 3) + v2) was refitted as y ~ v1 + v2; ranger hyperparameters were dropped. Formulas and fitted models are now honoured, refitted on each conformal split. Objects that cannot be refitted raise an error naming make_model() instead of silently substituting a default.
• conformal_aps() and conformal_raps() could return the full label set for every observation. The set builder included the class that *crossed* the threshold rather than inverting the calibrated score, and randomize = TRUE randomised the calibration scores but never the set construction. With oracle probabilities on a four-class problem, APS returned a mean set size of 3.90 out of 4 at 99.9% coverage; it now returns 2.69 at 88.6%.
• conformal_jackknife(), conformal_cv(), and predict() clamped the interval bounds to the smallest and largest order statistics when the quantile index fell outside 1..n. Barber et al. (2021) define those bounds as infinite, which occurs for fewer than 9 observations at alpha = 0.10. They now return -Inf / Inf, matching conformal_split().
• conformal_weighted() substituted the mean calibration weight for the test-point weight, so every test point received the same quantile. The new weights_new argument gives the exact procedure of Tibshirani et al. (2019), in which each test point receives its own quantile. Omitting it with non-uniform weights now warns.
• A fitted glm passed to any classification method failed with "missing columns for class levels", because the internal probability matrix was unnamed.
• coverage_by_bin() failed with "'breaks' are not unique" whenever predictions contained ties. Duplicate breaks are now collapsed, with a warning reporting the number of bins actually used.
• Conformal functions called set.seed() on the global random stream and left it altered. The seed argument now applies for the duration of the call only, and the user's .Random.seed is restored on exit. Seeded calls remain reproducible.
• plot() failed with "need finite 'ylim' values" on unbounded intervals. These are now drawn to the plot edge with a message.
• conformal_mondrian() and conformal_mondrian_class() silently substituted the pooled quantile for groups with fewer than three calibration points, voiding the group-conditional guarantee for exactly the groups that needed it. Such groups now receive an unbounded interval, with a warning naming the number of calibration points required.
• Data frames containing non-numeric columns produced the misleading error "must not contain NaN or Inf values". They now name the offending columns and suggest stats::model.matrix().

Changes in default behaviour

• conformal_aps() and conformal_raps() now default to randomize = TRUE, the method as published. Deterministic scoring (randomize = FALSE) remains available and now warns when the conformal quantile saturates at 1. Pass seed for reproducible randomised sets.
• Prediction sets are now the exact inversion of the calibrated score. New allow_empty argument on conformal_lac(), conformal_aps(), conformal_raps(), conformal_class_split(), and conformal_mondrian_class(); the default FALSE keeps the previous behaviour of replacing an empty set with the most probable class.

Other changes

• conformal_cqr()'s quantiles argument previously had no effect. It is now validated, recorded on the returned object, and checked for consistency with alpha.
• conformal_cv() and conformal_jackknife() now validate that x_new has the same number of columns as x.
• Jackknife+ prediction makes one call to predict_fun per leave-one-out model rather than one per (model, test point) pair.
• conformal_cv(x_new = NULL) records train_approximation = TRUE, and print() states that those intervals do not carry the CV+ guarantee.
• inst/CITATION now reports the installed version rather than a hardcoded one.
• paper/, Makefile, and llms*.txt are excluded from the source tarball, which removes an R CMD check WARNING about GNU extensions in paper/slides/Makefile and cuts the tarball from 4.2 MB.
• README and the accompanying paper: corrected the CRAN status, dependency count, and competitor versions, and softened the Mondrian and ACI exclusivity claims (see conformalForecast and AdaptiveConformal).