HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
ggdist vs MachineShop
A side-by-side editorial comparison of ggdist and MachineShop — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ggdist vs MachineShop: 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 MachineShop?
A mature R modelling framework refining variable importance and resampling controls
MachineShop provides a unified interface over a wide set of R model packages, handling fitting, resampling, performance metrics and variable importance behind one API. Recent releases are narrow and mostly corrective: 3.9.2 removed dead documentation links and fixed a Java parameter in a BART example, 3.9.1 ensured global settings reach compute nodes when varimp() runs in parallel and patched XGBoost model compatibility. The last release with real surface change was 3.9.0, which added offset support to XGBModel and a pool argument to calibration() controlling whether calibration curves are computed on pooled predictions or averaged across resampling iterations.
ggdist vs MachineShop: 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.
MachineShop
0.0INFRA · APIS
A mature R modelling framework refining variable importance and resampling controls
◆ Current state
MachineShop provides a unified interface over a wide set of R model packages, handling fitting, resampling, performance metrics and variable importance behind one API. Recent releases are narrow and mostly corrective: 3.9.2 removed dead documentation links and fixed a Java parameter in a BART example, 3.9.1 ensured global settings reach compute nodes when varimp() runs in parallel and patched XGBoost model compatibility. The last release with real surface change was 3.9.0, which added offset support to XGBModel and a pool argument to calibration() controlling whether calibration curves are computed on pooled predictions or averaged across resampling iterations.
◆ Where it's heading
Development has concentrated on variable importance and resampling rather than on adding models. 3.8.0 restructured the VariableImportance class to record which method and metric produced it, with an update() method to migrate objects from earlier versions, and extended term-specific p-values to Cox, POLR and survival regression models. 3.7.0 added grouped and stratified resampling to the control objects. The pace has slowed markedly - four releases in the last two years against six in the two before - and the recent content is compatibility work against XGBoost, parsnip, ggplot2 and recipes.
◆ Prediction
Expect the deprecated calibration pooling behaviour to be removed in a future release as the notes state, with the intervening versions continuing to track upstream model package changes.
Alternatives to ggdist and MachineShop
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 MachineShop.
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 MachineShop alternatives →
Recent activity from ggdist and MachineShop
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5mo agoMachineShopDocumentation link cleanup and a BART example fix
- 8mo agoMachineShopGlobal settings now reach compute nodes during parallel varimp
- 1y agoMachineShopOffset support for XGBoost and per-iteration calibration curves
- 1y agoggdistPer-geometry thickness subscales and settable defaults
- 1y agoMachineShopVariable importance objects record their own method and metric
- 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator ⚡
- 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
- 2y agoMachineShopGrouped and stratified resampling in the control objects
- 3y agoggdistBounded density becomes the default; existing charts change ⚡
- 3y agoMachineShopBackward compatibility for older model objects
- 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 MachineShop?
Both compete on the same themes — r-package — within Infra & APIs. ggdist and MachineShop 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 ggdist better than MachineShop?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggdist and MachineShop 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 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 MachineShop?
Top MachineShop alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "MachineShop alternatives" section above for the current picks, or visit /alternatives/machineshop for the full list with editorial commentary on each.