rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of ggstatsplot and spatstat — release velocity, themes, recent moves, and the top alternatives to consider.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
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.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
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 ggstatsplot 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 ggstatsplot 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. ggstatsplot 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. ggstatsplot 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 ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot 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.