mlr3mbo
mlr3mbo picked its defaults from a benchmark study, not from taste
A side-by-side editorial comparison of bayesplot and easystats — 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.
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.
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.
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.
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 easystats.
mlr3mbo picked its defaults from a benchmark study, not from taste
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
mlr3fselect turned feature selection into an asynchronous, distributable job
lime survives on compatibility patches years after its research moment
mlr3measures is systematically retrofitting sample weights across every metric
mlr3cluster went from a handful of clusterers to covering the field
See all bayesplot alternatives → · See all easystats 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 easystats 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 easystats 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 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.