cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of dcurves and hubExamples — release velocity, themes, recent moves, and the top alternatives to consider.
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
dcurves implements decision curve analysis — evaluating a prediction model or diagnostic test by net benefit across the range of thresholds a clinician might plausibly use, rather than by a single discrimination statistic. Its API stabilised in 2022 around dca() and test_consequences(). The two releases since exist because gtsummary and CRAN documentation rules changed, not because the method did.
Example data for the hubverse, moving whenever the standards it demonstrates move.
hubExamples ships the reference datasets that hubverse vignettes and downstream packages use to demonstrate forecast and target data. Its releases track the hubverse specification rather than any independent roadmap: 1.0.0 exists because the target time series standard changed, and 0.1.0 because the oracle output terminology did. The current release, 1.0.1, is a single fix for column deserialisation on systems without arrow.
dcurves implements decision curve analysis — evaluating a prediction model or diagnostic test by net benefit across the range of thresholds a clinician might plausibly use, rather than by a single discrimination statistic. Its API stabilised in 2022 around dca() and test_consequences(). The two releases since exist because gtsummary and CRAN documentation rules changed, not because the method did.
The package reached its intended scope quickly and then stopped. Its 2022 releases did the substantive work: adding threshold-level diagnostic accuracy, tightening argument validation, and taking one breaking change to make net-interventions-avoided plots show the treat-all and treat-none reference lines by default. Since then it has moved only as a dependent of the wider tidy-modelling documentation ecosystem it plugs into.
Nothing in these entries points to method or API work; expect the next release to be another compatibility or CRAN documentation patch.
hubExamples ships the reference datasets that hubverse vignettes and downstream packages use to demonstrate forecast and target data. Its releases track the hubverse specification rather than any independent roadmap: 1.0.0 exists because the target time series standard changed, and 0.1.0 because the oracle output terminology did. The current release, 1.0.1, is a single fix for column deserialisation on systems without arrow.
This is a downstream member of the hubverse package family, alongside hubUtils, hubData and hubValidations, and it moves when they define something new. The pattern across all four entries is the same: a standard changes upstream, hubExamples updates its data objects and vignettes to match. Sibling package hubAdmin has not shipped since November 2025, so the cohort is not currently in a coordinated wave.
The next release will most likely follow the next hubverse data-standard revision rather than lead it.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either dcurves or hubExamples.
A choice-based IRT model published once in 2019 and kept compiling ever since
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
Rebuilding SAS's formatting layer in R, one format specification at a time
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
Stream-network spatial models learning to run on data that no longer fits in memory
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all dcurves alternatives → · See all hubExamples alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. dcurves and hubExamples are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dcurves and hubExamples are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top dcurves alternatives in Analytics are ranked by recent ship velocity. Browse the "dcurves alternatives" section above for the current picks, or visit /alternatives/dcurves for the full list with editorial commentary on each.
Top hubExamples alternatives in Analytics are ranked by recent ship velocity. Browse the "hubExamples alternatives" section above for the current picks, or visit /alternatives/hubexamples for the full list with editorial commentary on each.