rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of distributions3 and gtsummary — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | distributions3 | gtsummary |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 2.5 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | r-package, probability-distributions, statistical-modelling, maintainership | clinical-tables, analysis-results-data, regression-summaries, reproducible-reporting |
| Last editorial update | 51m ago | 1h ago |
| Website | Visit → | Visit → |
distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.
An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.
An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.
The package's growth has come in two modes. Early releases absorbed whole families of distributions from outside contributors — the extreme-value set, Erlang, later the Poisson binomial — while later ones tightened the interface itself with is_discrete() and is_continuous() generics and elementwise type-safety when applying a distribution vector to a numeric vector. The handover is the notable event in the current window: maintenance moves to the author of the surrounding statistical ecosystem this package already integrates with through prodist() and countreg, which suggests the interface work will continue over the distribution-collection work.
Expect closer alignment with Zeileis's own packages, with prodist() coverage widening to more model classes; the entries here do not indicate whether new distribution families remain on the agenda.
gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.
The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.
Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.
Other Analytics 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 distributions3 or gtsummary.
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
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See all distributions3 alternatives → · See all gtsummary alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. distributions3 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 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 Analytics products to evaluate alongside.
Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.
Top gtsummary alternatives in Analytics are ranked by recent ship velocity. Browse the "gtsummary alternatives" section above for the current picks, or visit /alternatives/gtsummary-r for the full list with editorial commentary on each.