easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
Comparison · Analytics
bayestestR vs pins
A side-by-side editorial comparison of bayestestR and pins — release velocity, themes, recent moves, and the top alternatives to consider.
bayestestR vs pins: 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 pins?
pins keeps adding a storage backend per release while retiring its original API
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
bayestestR vs pins: 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.
pins
0.0ANALYTICS
pins keeps adding a storage backend per release while retiring its original API
◆ Current state
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
◆ Where it's heading
Two long-running processes, neither dramatic. Backend coverage expands toward wherever teams already store artifacts, which increasingly means Databricks and cloud object storage rather than a shared drive. Meanwhile the legacy pin() API from before the board model has been in a staged deprecation across at least three releases, escalated each time rather than removed.
◆ Prediction
Expect another board or two as storage platforms are requested, and the legacy pin() functions to finally become errors; the format list will keep tracking whichever serializer the R community settles on.
Alternatives to bayestestR and pins
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 pins.
discrim
discrim settled into a thin engine shim after handing its model definitions to parsnip.
dbparser
dbparser shed its database and CSV writers to become just a DrugBank parser.
desirability2
desirability2 is making multi-metric model selection a first-class tidymodels step.
crosstalk
crosstalk is frozen infrastructure: four releases in five years, mostly CRAN upkeep.
cmdstanr
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
See all bayestestR alternatives → · See all pins alternatives →
Recent activity from bayestestR and pins
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
- 5mo agopinsqs2 replaces qs; pins can be written in multiple formats
- 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 agopinsPin previews on Connect; Databricks host normalization
- 1y agobayestestRTail ESS returned from effective_sample() and its callers
- 1y agopinsAdds board_databricks() and switches parquet to nanoparquet
- 2y agopinspin_write() arguments must be named; Connect caches removed
- 2y agopinsMessage clarity and Google Drive dribble handling
- 2y agopinsboard_gdrive() added; cache location configurable
Frequently asked questions
What is the difference between bayestestR and pins?
They serve adjacent needs but don't currently overlap on shipped themes. bayestestR and pins 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 pins?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestestR and pins 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 pins?
Top pins alternatives in Analytics are ranked by recent ship velocity. Browse the "pins alternatives" section above for the current picks, or visit /alternatives/pins-r for the full list with editorial commentary on each.