tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of easystats and probably — release velocity, themes, recent moves, and the top alternatives to consider.
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
easystats is the meta-package for the easystats ecosystem, which spans insight, parameters, performance and their siblings. It ships almost no statistics of its own; its releases add installation helpers, ecosystem introspection functions and vignettes. The consequential release in this window is 0.7.0, which moved the whole ecosystem to an MIT license.
The package that made calibration a step instead of an afterthought.
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
easystats is the meta-package for the easystats ecosystem, which spans insight, parameters, performance and their siblings. It ships almost no statistics of its own; its releases add installation helpers, ecosystem introspection functions and vignettes. The consequential release in this window is 0.7.0, which moved the whole ecosystem to an MIT license.
Work concentrates on making the ecosystem legible and installable as a unit: easystats_packages() to enumerate it, easystats_citations() to count its citations, pak and r-universe support to install it, and a complete-workflow vignette to show it in use. Underneath that, 0.7.0 settled the licensing and formalized the author list. The pattern is a project tending its own boundaries rather than adding capability.
The recent additions are all introspection and installation helpers, so the next release most likely adds another of those or refreshes component versions rather than changing what the ecosystem does.
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
The recent releases are about making these objects survive leaving the session. butcher and required_pkgs() methods are what a model needs to be pinned, containerised and served, and their arrival alongside workflows adding a tailor postprocessing stage and vetiver adding probably support points the same way: calibration is being moved out of analysis scripts and into the deployed pipeline. The cal_*_none() reference implementations are the tell that calibration is now something people tune rather than apply once.
Expect the calibration functions to be reachable directly from a tuned workflow's postprocessing stage rather than applied to predictions afterwards, following the tailor integration that workflows just shipped.
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 easystats or probably.
Finished, widely taught, and shipping roxygen fixes.
Text features finally stay sparse all the way to the model.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
patchwork stopped being a ggplot composer and became a page composer.
See all easystats alternatives → · See all probably alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. easystats and probably 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. easystats and probably 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 easystats alternatives in Analytics are ranked by recent ship velocity. Browse the "easystats alternatives" section above for the current picks, or visit /alternatives/easystats for the full list with editorial commentary on each.
Top probably alternatives in Analytics are ranked by recent ship velocity. Browse the "probably alternatives" section above for the current picks, or visit /alternatives/probably for the full list with editorial commentary on each.