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Comparison · Analytics
bayestestR vs mlr3viz
A side-by-side editorial comparison of bayestestR and mlr3viz — release velocity, themes, recent moves, and the top alternatives to consider.
bayestestR vs mlr3viz: 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 mlr3viz?
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.
bayestestR vs mlr3viz: 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.
mlr3viz
2.5ANALYTICS
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
◆ Current state
mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.
◆ Where it's heading
The package is being narrowed toward generic plotting infrastructure while learner-specific plots migrate to the packages that own those learners. What it does add is access rather than new charts — passing parameters through to precrec::autoplot(), better hints when the wrong autoplot type is requested, and a confidence-interval plot for mlr3inferr. Determinism across ggplot2 versions has become a recurring concern, which is what happens when a visualization package is depended on by documentation and tests.
◆ Prediction
Following the Cox proportional-hazards precedent, further learner-specific plots are likely to move to their owning packages, leaving mlr3viz with the cross-cutting result objects.
Alternatives to bayestestR and mlr3viz
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 mlr3viz.
posterior
posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.
rredlist
rredlist threw out its species-centric API in 1.0.0 and rebuilt around assessments.
esquisse
esquisse's 1.0 turned a point-and-click addin into embeddable Shiny modules.
mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
See all bayestestR alternatives → · See all mlr3viz alternatives →
Recent activity from bayestestR and mlr3viz
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18d agomlr3vizmlr3viz 0.11.1 pins legend order for deterministic plots
- 2mo agobayestestRmcse() gains a centrality argument
- 2mo agobayestestRCmdStanFit support and tail-ESS as the default diagnostic
- 5mo agomlr3vizmlr3viz 0.11.0 quiets ggplot2 fortify warnings on ROC curves
- 11mo agobayestestRrope() gains complement probabilities; display() methods added
- 1y agomlr3vizmlr3viz 0.10.1 passes plotting parameters through to precrec
- 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
- 1y agomlr3vizmlr3viz 0.10.0 adds a LearnerSurvCoxPH plot
- 2y agomlr3vizmlr3viz 0.9.0 adds EnsembleFSResult plots
- 2y agomlr3vizmlr3viz 0.8.0 tracks paradox 1.0.0
Frequently asked questions
What is the difference between bayestestR and mlr3viz?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3viz is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is bayestestR better than mlr3viz?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3viz is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 mlr3viz?
Top mlr3viz alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3viz alternatives" section above for the current picks, or visit /alternatives/mlr3viz for the full list with editorial commentary on each.