easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
A side-by-side editorial comparison of bayestestR and yardstick — release velocity, themes, recent moves, and the top alternatives to consider.
Bayesian diagnostics get stricter defaults while the Stan backend list widens
bayestestR is the diagnostics and hypothesis-testing layer of the easystats stack, and its recent releases have concentrated on two things: reporting the right uncertainty numbers by default, and accepting posterior draws from more sources. The 0.18.x line added CmdStanFit support alongside the existing rstanarm/brms paths and switched effective-sample-size reporting to tail-ESS. Bug-fix releases in between are mostly CRAN-check maintenance.
yardstick made fairness metrics a first-class part of tidymodels evaluation
yardstick supplies the metrics tidymodels evaluates models with. Its recent history is metric expansion into areas the package did not originally cover - survival analysis, model fairness, and in 1.4.0 a batch of regression and classification metrics filling remaining gaps - alongside a long deprecation cycle that finally turned errors on in 1.4.0.
bayestestR is the diagnostics and hypothesis-testing layer of the easystats stack, and its recent releases have concentrated on two things: reporting the right uncertainty numbers by default, and accepting posterior draws from more sources. The 0.18.x line added CmdStanFit support alongside the existing rstanarm/brms paths and switched effective-sample-size reporting to tail-ESS. Bug-fix releases in between are mostly CRAN-check maintenance.
The package is converging on a single posture: work with raw MCMC draws from anywhere, and report the diagnostic that actually governs the interval being shown. Successive releases have swapped defaults rather than added surface area, and the efficiency work in 0.16.x aimed squarely at large brms and rstanarm fits. Output formatting is drifting toward the shared easystats display() and tinytable path.
Expect continued backend coverage on the Stan side and further alignment of print/display behavior with insight and the rest of easystats; the entries do not show a push into new inference methods.
yardstick supplies the metrics tidymodels evaluates models with. Its recent history is metric expansion into areas the package did not originally cover - survival analysis, model fairness, and in 1.4.0 a batch of regression and classification metrics filling remaining gaps - alongside a long deprecation cycle that finally turned errors on in 1.4.0.
The direction is coverage plus extensibility. Rather than adding fairness metrics one at a time, 1.3.0 shipped new_groupwise_metric() so group-aware metrics can be defined for the problem at hand, which is the more durable contribution. The parallel thread is removing hidden state: the event_first global option, deprecated in 0.0.7, took until 1.4.0 to become an error.
Expect the groupwise constructor to attract more fairness definitions than the three shipped, and the developer-facing metric creation helpers deprecated in 1.2.0 to be removed next; core metric coverage now looks close to complete.
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 bayestestR or yardstick.
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.
See all bayestestR alternatives → · See all yardstick alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. bayestestR and yardstick 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. bayestestR and yardstick 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 bayestestR alternatives in Analytics are ranked by recent ship velocity. Browse the "bayestestR alternatives" section above for the current picks, or visit /alternatives/bayestestr for the full list with editorial commentary on each.
Top yardstick alternatives in Analytics are ranked by recent ship velocity. Browse the "yardstick alternatives" section above for the current picks, or visit /alternatives/yardstick for the full list with editorial commentary on each.