HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
ggdist vs mize
A side-by-side editorial comparison of ggdist and mize — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ggdist vs mize: 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 mize?
A numerical optimization toolkit that has been feature-complete and quiet since 2017
mize provides a configurable interface to unconstrained numerical optimization methods - line searches, gradient descent variants, quasi-Newton updates - usable both as a one-shot call and as a stepwise iterator. Its functional surface has not changed since the initial CRAN release in July 2017. Every release since has been a patch: R-devel compatibility, line search edge cases, and in 2026's 0.2.5 the removal of LazyData from DESCRIPTION plus deletion of some flaky tests.
ggdist vs mize: 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.
mize
0.0INFRA · APIS
A numerical optimization toolkit that has been feature-complete and quiet since 2017
◆ Current state
mize provides a configurable interface to unconstrained numerical optimization methods - line searches, gradient descent variants, quasi-Newton updates - usable both as a one-shot call and as a stepwise iterator. Its functional surface has not changed since the initial CRAN release in July 2017. Every release since has been a patch: R-devel compatibility, line search edge cases, and in 2026's 0.2.5 the removal of LazyData from DESCRIPTION plus deletion of some flaky tests.
◆ Where it's heading
The pattern is a stable library rather than an abandoned one. Fixes address real reports - a bracket_step error when the Schmidt line search exhausts its function evaluation budget, an incorrect gradient count under backtracking with a specified step_down - and the maintainer used one release note to clarify that backtracking behaviour differs depending on whether step_down is supplied, which reads as answering a recurring question. The five and a half year gap between 0.2.4 and 0.2.5 is the clearest signal: the package is maintained on demand, not developed.
◆ Prediction
Expect nothing until an R or CRAN policy change forces another compliance patch, which is what triggered the most recent release.
Alternatives to ggdist and mize
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 mize.
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.
Recent activity from ggdist and mize
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agomizeCRAN compliance patch after five years of silence
- 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
- 5y agomizeBacktracking line search reporting and documentation fix
- 6y agomizeR-devel compatibility fix for class checking
- 7y agomizeSchmidt line search error when the evaluation budget is exhausted
- 7y agomizeStage check fix for bold driver and backtracking
- 9y agomizeCRAN release 0.1.1
Frequently asked questions
What is the difference between ggdist and mize?
Both compete on the same themes — r-package — within Infra & APIs. ggdist and mize 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 mize?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggdist and mize 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 mize?
Top mize alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mize alternatives" section above for the current picks, or visit /alternatives/mize for the full list with editorial commentary on each.