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rstanarm vs tidyclust

A side-by-side editorial comparison of rstanarm and tidyclust — release velocity, themes, recent moves, and the top alternatives to consider.

rstanarm vs tidyclust: at a glance

Featurerstanarmtidyclust
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbayesian, stan, regression-models, dependency-migrationtidyclust, clustering, tidymodels, dbscan
Last editorial update56m ago1h ago
WebsiteVisit →Visit →

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.

Read the full rstanarm trajectory →

What is tidyclust?

tidyclust just tripled the model types it can fit, and handed finalization back to tune

tidyclust brings clustering into the tidymodels interface, and 0.3.0 was the release where its model coverage stopped being k-means and hierarchical clustering. DBSCAN and HDBSCAN, Gaussian mixtures, and mean shift all arrived at once as proper clustering specifications. The two releases since have been bug fixes on the metric and sparse-data paths, which is the usual pattern after a large surface addition.

Read the full tidyclust trajectory →

rstanarm vs tidyclust: editorial side-by-side

R
rstanarm
ANALYTICS
0.0

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.

T
tidyclust
ANALYTICS
0.0

tidyclust just tripled the model types it can fit, and handed finalization back to tune

◆ Current state

tidyclust brings clustering into the tidymodels interface, and 0.3.0 was the release where its model coverage stopped being k-means and hierarchical clustering. DBSCAN and HDBSCAN, Gaussian mixtures, and mean shift all arrived at once as proper clustering specifications. The two releases since have been bug fixes on the metric and sparse-data paths, which is the usual pattern after a large surface addition.

◆ Where it's heading

The package is converging with the rest of tidymodels rather than maintaining a parallel API: finalize_model_tidyclust() and finalize_workflow_tidyclust() are deprecated because tune::finalize_model() and tune::finalize_workflow() now handle cluster_spec objects natively. That removes the last place where clustering needed its own version of a shared verb. With density-based and model-based clustering now present, the interface has to cover model families with genuinely different assumptions than the centroid methods it started with.

◆ Prediction

The recent fixes to cluster_metric_set() labeling and custom-metric authoring suggest evaluation is the current focus, so metrics suited to density-based clusters are the likely next addition.

Alternatives to rstanarm and tidyclust

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 rstanarm or tidyclust.

See all rstanarm alternatives → · See all tidyclust alternatives →

Recent activity from rstanarm and tidyclust

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agotidyclusttidyclust 0.3.2 fixes k_means() on sparse predictors
  2. 1mo agotidyclusttidyclust 0.3.1 stops same-named metrics silently merging
  3. 2mo agotidyclusttidyclust 0.3.0 adds DBSCAN, Gaussian mixture, and mean shift models
  4. 10mo agorstanarmrstanarm 2.32.2 migrates formula machinery to reformulas
  5. 1y agotidyclusttidyclust 0.2.4 switches distance calculations to philentropy
  6. 2y agotidyclusttidyclust 0.2.3 resolves a clustMixType reverse-dependency issue
  7. 2y agotidyclusttidyclust 0.2.2 resolves a ClusterR reverse-dependency issue
  8. 2y agorstanarmrstanarm 2.32.1 fixes unit_vector error, enables LTO
  9. 2y agorstanarmrstanarm 2.26.1 adopts new rstan syntax and as_draws()
  10. 4y agorstanarmrstanarm 2.21.3 fixes loo() and adds stan_jm offsets
  11. 6y agorstanarmrstanarm 2.21.1 changes default prior behaviour

Frequently asked questions

What is the difference between rstanarm and tidyclust?

They serve adjacent needs but don't currently overlap on shipped themes. rstanarm and tidyclust 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 rstanarm better than tidyclust?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rstanarm and tidyclust 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 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.

What are the best alternatives to tidyclust?

Top tidyclust alternatives in Analytics are ranked by recent ship velocity. Browse the "tidyclust alternatives" section above for the current picks, or visit /alternatives/tidyclust for the full list with editorial commentary on each.