rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of gtsummary and spatstat — release velocity, themes, recent moves, and the top alternatives to consider.
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.
The spatstat umbrella package, now mostly a pointer to the sub-packages doing the work
spatstat is the front package of a family that was split into specialised components — spatstat.geom, spatstat.random, spatstat.model, spatstat.explore, spatstat.univar and spatstat.sparse. Its own release notes reflect that: entries in this window are largely announcements of where the real changes landed, plus documentation and cross-reference maintenance. The codebase it fronts passed 200,000 lines as of 3.5-1.
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.
spatstat is the front package of a family that was split into specialised components — spatstat.geom, spatstat.random, spatstat.model, spatstat.explore, spatstat.univar and spatstat.sparse. Its own release notes reflect that: entries in this window are largely announcements of where the real changes landed, plus documentation and cross-reference maintenance. The codebase it fronts passed 200,000 lines as of 3.5-1.
The split is effectively complete and the umbrella's role has settled into coordination — tracking version dependencies across sub-packages and pointing users to them. The family has kept subdividing over this period, with spatstat.univar joining in 3.1-0. The one substantive user-facing addition here is documentation infrastructure: 3.3-0 added the ability to list the history of changes to a specific function, which is a navigational answer to a codebase now spread across many packages.
Expect this package's notes to continue summarising sub-package activity rather than carrying features of its own, since every release in this window does exactly that. Read spatstat.geom, spatstat.random and spatstat.model for the substance.
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 gtsummary or spatstat.
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all gtsummary alternatives → · See all spatstat alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. gtsummary and spatstat 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. gtsummary and spatstat 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 Analytics products to evaluate alongside.
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.
Top spatstat alternatives in Analytics are ranked by recent ship velocity. Browse the "spatstat alternatives" section above for the current picks, or visit /alternatives/spatstat-r for the full list with editorial commentary on each.