HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of bkmrhat and ggdist — release velocity, themes, recent moves, and the top alternatives to consider.
A parallel-chain helper for bkmr that has settled into pure upkeep.
bkmrhat wraps Bayesian kernel machine regression (bkmr) so users can run and diagnose multiple MCMC chains in parallel, then combine or continue them. The functional surface has been stable since 2022, when chain-combining picked up a low-memory path and a seed-collision bug was corrected. The most recent release adds only diagnostic metadata to the package description.
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.
bkmrhat wraps Bayesian kernel machine regression (bkmr) so users can run and diagnose multiple MCMC chains in parallel, then combine or continue them. The functional surface has been stable since 2022, when chain-combining picked up a low-memory path and a seed-collision bug was corrected. The most recent release adds only diagnostic metadata to the package description.
Three releases across five years, and the newest carries no user-facing change at all. The package is in maintenance: it does what it set out to do for bkmr users, and updates now arrive only when CRAN or an upstream dependency forces them.
Expect the next release to be another compliance or dependency-driven patch rather than new functionality; the entries show no in-progress feature work.
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.
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 bkmrhat or ggdist.
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 bkmrhat alternatives → · See all ggdist alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — bayesian-statistics, r-package — within Infra & APIs. bkmrhat and ggdist 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. bkmrhat and ggdist 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 bkmrhat alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "bkmrhat alternatives" section above for the current picks, or visit /alternatives/bkmrhat for the full list with editorial commentary on each.
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.