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Comparison · Analytics
bayestestR vs rstanarm
A side-by-side editorial comparison of bayestestR and rstanarm — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:bayesianstan
bayestestR vs rstanarm: at a glance
What is bayestestR?
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.
What is rstanarm?
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
2.32.2 is entirely infrastructure and dependency work: formula machinery migrated from lme4 to reformulas, `r_eff` no longer computed for loo by default, the Stan R packages repo replaced by R-Universe, rstantools adopted to fix build and export errors, and CRAN NOTE cleanups — contributed largely by four first-time contributors. 2.32.1 and 2.26.1 follow the same pattern, tracking rstan syntax and adding `posterior::as_draws()` support. The last release with substantive modelling content is 2.21.1, which changed how default priors are determined and flipped `autoscale` to FALSE outside default priors.
bayestestR vs rstanarm: editorial side-by-side
bayestestR
0.0ANALYTICS
Bayesian diagnostics get stricter defaults while the Stan backend list widens
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
rstanarm
0.0ANALYTICS
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
◆ Current state
2.32.2 is entirely infrastructure and dependency work: formula machinery migrated from lme4 to reformulas, `r_eff` no longer computed for loo by default, the Stan R packages repo replaced by R-Universe, rstantools adopted to fix build and export errors, and CRAN NOTE cleanups — contributed largely by four first-time contributors. 2.32.1 and 2.26.1 follow the same pattern, tracking rstan syntax and adding `posterior::as_draws()` support. The last release with substantive modelling content is 2.21.1, which changed how default priors are determined and flipped `autoscale` to FALSE outside default priors.
◆ Where it's heading
The package has moved from feature development into ecosystem maintenance, and the contributor list shows why it survives: outside developers keep it compiling against a moving Stan, lme4 and CRAN. The `as_draws()` support and the reformulas migration both point the same way — rstanarm increasingly consumes shared infrastructure (posterior, reformulas, rstantools) instead of carrying its own.
◆ Prediction
Expect the next release to track another upstream change — rstan, reformulas or CRAN policy — rather than add model families. The pre-fit model surface looks settled.
Alternatives to bayestestR and rstanarm
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 rstanarm.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
taxize
taxize spends its releases absorbing other people's API changes, one dead source at a time.
See all bayestestR alternatives → · See all rstanarm alternatives →
Recent activity from bayestestR and rstanarm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agobayestestRmcse() gains a centrality argument
- 2mo agobayestestRCmdStanFit support and tail-ESS as the default diagnostic
- 10mo agorstanarmrstanarm 2.32.2 migrates formula machinery to reformulas
- 11mo agobayestestRrope() gains complement probabilities; display() methods added
- 1y agobayestestRdescribe_posterior() efficiency and multinomial handling
- 1y agobayestestReffects argument changes behavior for large brms/rstanarm fits
- 1y agobayestestRTail ESS returned from effective_sample() and its callers
- 2y agorstanarmrstanarm 2.32.1 fixes unit_vector error, enables LTO
- 2y agorstanarmrstanarm 2.26.1 adopts new rstan syntax and as_draws()
- 4y agorstanarmrstanarm 2.21.3 fixes loo() and adds stan_jm offsets
- 6y agorstanarmrstanarm 2.21.1 changes default prior behaviour
Frequently asked questions
What is the difference between bayestestR and rstanarm?
Both compete on the same themes — bayesian, stan — within Analytics. bayestestR and rstanarm 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.
Is bayestestR better than rstanarm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestestR and rstanarm 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.
What are the best alternatives to bayestestR?
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.
What are the best alternatives to rstanarm?
Top rstanarm alternatives in Analytics are ranked by recent ship velocity. Browse the "rstanarm alternatives" section above for the current picks, or visit /alternatives/rstanarm for the full list with editorial commentary on each.