easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
A side-by-side editorial comparison of ggpubr and tune — release velocity, themes, recent moves, and the top alternatives to consider.
ggpubr reached 1.0.0 with p-value formatting presets for specific journals
ggpubr adds publication-ready statistics and annotation to ggplot2. Two releases define its capability: 0.5.0 introduced the stat_*_test family and geom_pwc() for pairwise comparison brackets, and 1.0.0 added p-value formatting presets matching named journal house styles. In between, most releases are ggplot2 and dplyr deprecation chasing.
tune extends tuning past the model itself to postprocessors, and adds a second parallel backend
tune runs hyperparameter search for tidymodels. Version 2.0.0 rewrote tune_grid() to make postprocessing tunable alongside preprocessing and the model, changed the .config naming scheme to match, and added mirai as a parallel backend next to future. Version 2.1.0 followed with quantile regression support and a replacement Gaussian process engine.
ggpubr adds publication-ready statistics and annotation to ggplot2. Two releases define its capability: 0.5.0 introduced the stat_*_test family and geom_pwc() for pairwise comparison brackets, and 1.0.0 added p-value formatting presets matching named journal house styles. In between, most releases are ggplot2 and dplyr deprecation chasing.
The package is moving from drawing statistics to matching the conventions of where they get published - style presets are a different kind of feature from a new test. That sits on a persistent maintenance load: after_stat migrations, linewidth parameters, R-devel changing how the Wilcoxon test handles ties. ggpubr absorbs upstream deprecations so that figure code written years ago keeps rendering.
Expect the preset list to grow as users request their own journals' conventions, and the deprecation-chasing to continue with each ggplot2 release; the statistical test coverage looks complete enough that additions there would be surprising.
tune runs hyperparameter search for tidymodels. Version 2.0.0 rewrote tune_grid() to make postprocessing tunable alongside preprocessing and the model, changed the .config naming scheme to match, and added mirai as a parallel backend next to future. Version 2.1.0 followed with quantile regression support and a replacement Gaussian process engine.
Two migrations run through this timeline. The tunable surface keeps widening - first censored regression as a mode, then postprocessors via tailor - so that a candidate is now a preprocessor, model and postprocessor triple rather than just a model. The parallel story has moved from foreach to future and now to mirai, each step deprecating the last. Neither is finished.
Expect the foreach path to be removed outright, and the postprocessing surface to grow as tailor gains more steps; the GauPro switch will likely need follow-up as its behavior differs from the old engine.
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 ggpubr or tune.
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
discrim settled into a thin engine shim after handing its model definitions to parsnip.
dbparser shed its database and CSV writers to become just a DrugBank parser.
desirability2 is making multi-metric model selection a first-class tidymodels step.
crosstalk is frozen infrastructure: four releases in five years, mostly CRAN upkeep.
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggpubr and tune 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. ggpubr and tune 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 ggpubr alternatives in Analytics are ranked by recent ship velocity. Browse the "ggpubr alternatives" section above for the current picks, or visit /alternatives/ggpubr for the full list with editorial commentary on each.
Top tune alternatives in Analytics are ranked by recent ship velocity. Browse the "tune alternatives" section above for the current picks, or visit /alternatives/tune for the full list with editorial commentary on each.