easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
A side-by-side editorial comparison of bayesplot and pins — release velocity, themes, recent moves, and the top alternatives to consider.
bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.
bayesplot supplies the plotting layer for Stan-adjacent Bayesian workflows: posterior predictive checks, MCMC diagnostics and LOO diagnostics. Releases through 2025 alternate between new plot families and keeping pace with ggplot2, which changed behavior twice in the visible window. Contributions increasingly arrive from outside the core Stan team.
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.
bayesplot supplies the plotting layer for Stan-adjacent Bayesian workflows: posterior predictive checks, MCMC diagnostics and LOO diagnostics. Releases through 2025 alternate between new plot families and keeping pace with ggplot2, which changed behavior twice in the visible window. Contributions increasingly arrive from outside the core Stan team.
Two forces drive the release line: expanding what can be checked visually, and absorbing upstream ggplot2 churn. The 1.13-1.14 pair shows the first, adding LOO-PIT ECDF plots, quantile dot plots and discrete-data handling across the stat family, while 1.12 and 1.15 are largely spent on ggplot2 3.6 and 4.0 compatibility. The recurring new-contributor lists suggest maintenance load is being spread rather than concentrated.
Discrete-data support has rolled out plot family by plot family across three releases; the next release most likely continues that sweep and finishes the ggplot2 v4 adaptation.
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.
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.
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.
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 bayesplot or pins.
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 bayesplot alternatives → · See all pins alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. bayesplot 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayesplot 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.
Top bayesplot alternatives in Analytics are ranked by recent ship velocity. Browse the "bayesplot alternatives" section above for the current picks, or visit /alternatives/bayesplot for the full list with editorial commentary on each.
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.