HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
ggdist vs simDAG
A side-by-side editorial comparison of ggdist and simDAG — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ggdist vs simDAG: at a glance
What is ggdist?
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
What is simDAG?
simDAG grew a second simulation engine, then spent two releases surviving upstream breakage.
simDAG generates data from directed acyclic graphs, with a library of node types covering Gaussian, binomial, Poisson, negative binomial, zero-inflated, ordered regression, Cox, and Aalen models. The 1.0.0 milestone opened node_cox() to arbitrary baseline hazard functions, which lets continuous time-dependent hazards drive discrete-event simulations. The two most recent releases exist only to keep the package on CRAN through breakage in lme4 and simr.
ggdist vs simDAG: editorial side-by-side
ggdist
0.0INFRA · APIS
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
◆ Current state
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
◆ Where it's heading
Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.
◆ Prediction
Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.
simDAG
2.5INFRA · APIS
simDAG grew a second simulation engine, then spent two releases surviving upstream breakage.
◆ Current state
simDAG generates data from directed acyclic graphs, with a library of node types covering Gaussian, binomial, Poisson, negative binomial, zero-inflated, ordered regression, Cox, and Aalen models. The 1.0.0 milestone opened node_cox() to arbitrary baseline hazard functions, which lets continuous time-dependent hazards drive discrete-event simulations. The two most recent releases exist only to keep the package on CRAN through breakage in lme4 and simr.
◆ Where it's heading
The package has been widening what a simulation can represent rather than deepening any one node. Networks arrived in 0.4.0 so individuals could depend on each other, discrete-event simulation in continuous time arrived in 0.5.0 as an alternative to the discrete-time engine, and 1.0.0 connected the two by letting continuous hazards feed the event-driven path. Alongside that, node types keep accumulating for outcome families the framework could not previously generate.
◆ Prediction
Expect the node library to keep expanding into outcome types the discrete-event engine can now support, though the recent releases suggest upstream dependency churn will keep consuming release slots.
Alternatives to ggdist and simDAG
Other Infra & APIs 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 ggdist or simDAG.
bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
estimatr
Fast design-based estimators for experiments, coasting on CRAN patches.
ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
ltertools
A column-key toolkit for stitching decades of ecological field data into one table.
finnts
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all ggdist alternatives → · See all simDAG alternatives →
Recent activity from ggdist and simDAG
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18d agosimDAGCRAN-retention patch for upstream lme4 breakage
- 3mo agosimDAGArbitrary baseline hazards connect node_cox() to discrete-event sims
- 4mo agosimDAGTest-only fix for an upstream simr update
- 5mo agosimDAGAdds node_polr() for ordinal outcomes and rsurv node support
- 7mo agosimDAGAdds continuous-time discrete-event simulation ⚡
- 10mo agosimDAGAdds link functions to node types and fixes a broken seed default
- 1y agoggdistPer-geometry thickness subscales and settable defaults
- 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator ⚡
- 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
- 3y agoggdistBounded density becomes the default; existing charts change ⚡
- 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
- 4y agoggdistComputed variables shared across sub-geometries
Frequently asked questions
What is the difference between ggdist and simDAG?
Both compete on the same themes — r-package — within Infra & APIs. simDAG is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is ggdist better than simDAG?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. simDAG is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to ggdist?
Top ggdist alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggdist alternatives" section above for the current picks, or visit /alternatives/ggdist for the full list with editorial commentary on each.
What are the best alternatives to simDAG?
Top simDAG alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "simDAG alternatives" section above for the current picks, or visit /alternatives/simdag for the full list with editorial commentary on each.