NEWS

iPEB 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()) { ... }.

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.