Changes in version 0.1.1 (2026-09-17)                  

  - Addressed CRAN reviewer feedback on the initial submission: removed
    the single quotes around the acronym PEB in the Description (quotes
    are reserved for package, software, and API names), and changed the
    run_app() example from \dontrun{} to if (interactive()) { ... }.

                        Changes in version 0.1.0                        

  - First release.
  - ipeb() and ipeb_run() accept an optional seed argument that fixes
    the internal validation split, making a fit exactly reproducible.
  - ipeb() fits the improved Parametric Empirical Bayes model on
    training data: a time-gap-aware standardization layer (random
    intercept, optional random slope, optional AR(1)/OU residual
    autocorrelation), optional covariate adjustment, objective-driven
    weighting (sensitivity, lead-time, or combined objective), optional
    feature selection, and an automatically chosen scalar or
    multivariate combiner.
  - predict() scores new subjects, and evaluate() reports per-patient
    sensitivity and lead time with per-visit specificity at user-chosen
    operating points.
  - ipeb_run() provides a one-call fit-and-evaluate wrapper.
  - ipeb_innovations() exposes the time-gap-aware standardization layer,
    so history-adjusted baselines can be built from the same layer as
    iPEB.
  - print(), summary(), and plot() methods for fitted ipeb objects.
  - Ships a small synthetic longitudinal example dataset, ipeb_example.