cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
dcurves vs tulpaRatio
A side-by-side editorial comparison of dcurves and tulpaRatio — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
dcurves vs tulpaRatio: at a glance
What is dcurves?
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.
What is tulpaRatio?
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
dcurves vs tulpaRatio: editorial side-by-side
dcurves
0.0ANALYTICS
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
Nothing in these entries points to method or API work; expect the next release to be another compatibility or CRAN documentation patch.
tulpaRatio
0.0ANALYTICS
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
◆ Current state
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
◆ Where it's heading
The feed reads as one architectural bet followed by the work to justify it. After the native backend landed, the releases are a steady march of gradient and adaptation work — hand-coded gradients for more model families, L-BFGS mass matrix adaptation, an O2 build — each measured as a speed multiple against Stan. Coverage is tracked openly as a fraction (48 of 60 hand-coded configs), and unresolved problems are named rather than buried, including a deferred GP spatial bug.
◆ Prediction
The hand-coded gradient coverage count is the visible backlog, so the next releases most likely close the remaining configs and resolve the GP spatial issue that the benchmark release explicitly deferred.
Alternatives to dcurves and tulpaRatio
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 tulpaRatio.
MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
fmtr
Rebuilding SAS's formatting layer in R, one format specification at a time
betaselectr
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
SSN2
Stream-network spatial models learning to run on data that no longer fits in memory
BiocManager
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all dcurves alternatives → · See all tulpaRatio alternatives →
Recent activity from dcurves and tulpaRatio
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agotulpaRatioHand-coded gradients reach binomial zero-inflated and hurdle models
- 6mo agotulpaRatioGaussian process sampling reaches roughly 4x Stan
- 7mo agotulpaRatioL-BFGS mass matrix adaptation for MSGP models
- 7mo agotulpaRatioBenchmarks published for 35 of 40 model configurations
- 7mo agotulpaRatioFirst stable release ships a native HMC/NUTS backend, no Stan required ⚡
- 9mo agodcurvesHTML5 documentation rebuild for CRAN
- 2y agodcurvesbroom.helpers added to Suggests for gtsummary 2.0
- 3y agodcurvesNet interventions plots now show treat-all and treat-none by default
- 4y agodcurvestest_consequences() reports accuracy across thresholds
Frequently asked questions
What is the difference between dcurves and tulpaRatio?
Both compete on the same themes — r-package — within Analytics. dcurves and tulpaRatio 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.
Is dcurves better than tulpaRatio?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dcurves and tulpaRatio 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.
What are the best alternatives to dcurves?
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.
What are the best alternatives to tulpaRatio?
Top tulpaRatio alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpaRatio alternatives" section above for the current picks, or visit /alternatives/tulparatio for the full list with editorial commentary on each.