cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of dcurves and r2dii.analysis — 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.
The climate-alignment maths behind PACTA, now stable and maintained rather than reshaped
r2dii.analysis computes the target-setting side of PACTA: market-share and sectoral decarbonisation targets that measure a loan book or portfolio against climate scenarios. It sits downstream of the matched company data the sibling packages produce. The 0.5.0 release declared it lifecycle-stable and handed maintenance to a new lead, and releases since have been narrow corrections rather than new methods.
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.
r2dii.analysis computes the target-setting side of PACTA: market-share and sectoral decarbonisation targets that measure a loan book or portfolio against climate scenarios. It sits downstream of the matched company data the sibling packages produce. The 0.5.0 release declared it lifecycle-stable and handed maintenance to a new lead, and releases since have been narrow corrections rather than new methods.
The history is a package converging. Early releases churn the output contract of target_market_share() and target_sda() — which sectors appear, which years, how missing production is treated — and each change alters the numbers users get. The ald-to-abcd rename runs across several releases before completing, and by 0.5.0 the churn has stopped, with three older summarise functions soft-deprecated and the package marked stable. What remains is edge-case correctness in target coverage.
With the package marked stable and the terminology migration finished, the soft-deprecated summarise functions are the obvious next thing to remove outright.
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 r2dii.analysis.
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 r2dii.analysis alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. dcurves and r2dii.analysis 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 r2dii.analysis 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 r2dii.analysis alternatives in Analytics are ranked by recent ship velocity. Browse the "r2dii.analysis alternatives" section above for the current picks, or visit /alternatives/r2dii-analysis for the full list with editorial commentary on each.