HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of ggdist and profoc — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A forecast combination package that spun its profiler out into its own project
profoc combines probabilistic forecasts online, using the Bernstein online aggregation family with B-spline smoothing over quantiles and time. The recent releases are infrastructure rather than method: 1.3.4 removed a using namespace arma directive for CRAN compliance and closed a timer edge case, 1.3.3 adjusted the integration with rcpptimer against its now-stable 1.2.0 API. The last release to change what users can do was 1.3.0, which exposed the conline C++ class to R and exported init_experts_list(), make_basis_mats(), make_hat_mats() and post_process_model() so the engine can be driven directly.
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.
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.
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.
profoc combines probabilistic forecasts online, using the Bernstein online aggregation family with B-spline smoothing over quantiles and time. The recent releases are infrastructure rather than method: 1.3.4 removed a using namespace arma directive for CRAN compliance and closed a timer edge case, 1.3.3 adjusted the integration with rcpptimer against its now-stable 1.2.0 API. The last release to change what users can do was 1.3.0, which exposed the conline C++ class to R and exported init_experts_list(), make_basis_mats(), make_hat_mats() and post_process_model() so the engine can be driven directly.
The direction is toward a reusable C++ core with thin language bindings. The timing code that lived inside profoc was extracted into the standalone rcpptimer package in 1.3.2, deliberately so other R packages and Python projects could use it through cpptimer and cppytimer, and the clock header was reworked in 1.3.1 to maximise the code shared between the R and Python versions. Method work sits earlier in the history - periodic splines and penalties in 1.2.0, the penalty() function in 1.1.0 - while the recent cadence, a single release in the last sixteen months, points at a package the maintainer considers finished.
The repeated references to future Python use suggest the next significant work happens outside this package, in the shared C++ components, rather than in profoc's R surface.
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 profoc.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all ggdist alternatives → · See all profoc alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. ggdist and profoc 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. ggdist and profoc 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.
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.
Top profoc alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "profoc alternatives" section above for the current picks, or visit /alternatives/profoc for the full list with editorial commentary on each.