bbotk
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
A side-by-side editorial comparison of ggpubr and insight — 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.
insight quietly widens the set of model objects the easystats ecosystem can read
insight is the extraction layer under the easystats packages — it answers what a fitted model's parameters, data, variance and priors are, for whatever object it is handed. The 1.4.x and 1.5.x releases read as a steady widening of that support list: tidymodels workflows, cmdstanr fits, rstpm2 survival models, lavaan variance-covariance, mice imputations.
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.
insight is the extraction layer under the easystats packages — it answers what a fitted model's parameters, data, variance and priors are, for whatever object it is handed. The 1.4.x and 1.5.x releases read as a steady widening of that support list: tidymodels workflows, cmdstanr fits, rstpm2 survival models, lavaan variance-covariance, mice imputations.
Two things move together here. The support list grows toward objects produced outside the easystats world, and performance work targets the helpers that everything else calls — compact_list(), is_empty_object(), find_parameters() on mgcv models. New functions appear occasionally (get_simulated(), vcovFPC()) but the center of gravity is coverage, not capability.
Expect further model classes to be added as downstream easystats packages need them, and continued alignment with R-devel behavior changes like the weighted-residuals revision.
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 insight.
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.
Contribution-driven maintenance on a package whose last structural change was magick support.
pins keeps adding a storage backend per release while retiring its original API
tsibble shipped one release in five and a half years - the data structure is finished
yardstick made fairness metrics a first-class part of tidymodels evaluation
See all ggpubr alternatives → · See all insight alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggpubr and insight 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 insight 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 insight alternatives in Analytics are ranked by recent ship velocity. Browse the "insight alternatives" section above for the current picks, or visit /alternatives/insight for the full list with editorial commentary on each.