rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
embed vs rstanarm
A side-by-side editorial comparison of embed and rstanarm — release velocity, themes, recent moves, and the top alternatives to consider.
embed vs rstanarm: at a glance
What is embed?
embed keeps adding encoding steps while shedding its deep-learning dependencies
embed supplies recipes steps that turn categorical predictors into numeric representations — likelihood encoding, UMAP projection, string-distance collapsing. The 1.1.x line made UMAP arguments tunable and moved keras and tensorflow out of hard dependencies; 1.2.0 added analytical likelihood encoding with partial pooling and retired step_feature_hash() in favor of textrecipes.
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.
embed vs rstanarm: editorial side-by-side
embed
0.0ANALYTICS
embed keeps adding encoding steps while shedding its deep-learning dependencies
◆ Current state
embed supplies recipes steps that turn categorical predictors into numeric representations — likelihood encoding, UMAP projection, string-distance collapsing. The 1.1.x line made UMAP arguments tunable and moved keras and tensorflow out of hard dependencies; 1.2.0 added analytical likelihood encoding with partial pooling and retired step_feature_hash() in favor of textrecipes.
◆ Where it's heading
Two quiet directions run through these releases. One is making the steps tunable rather than fixed, so they participate properly in tidymodels grids. The other is boundary maintenance: heavy dependencies pushed to Suggests, overlapping steps handed to the package that owns them. Recent releases are thin and fix-driven.
◆ Prediction
Expect further consolidation with textrecipes over which package owns which encoding step, and continued upkeep against xgboost and uwot releases rather than new step families.
rstanarm
0.0ANALYTICS
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.
Alternatives to embed and rstanarm
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 embed or rstanarm.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
taxize
taxize spends its releases absorbing other people's API changes, one dead source at a time.
See all embed alternatives → · See all rstanarm alternatives →
Recent activity from embed and rstanarm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agoembedstep_umap() zero-component bug fixed
- 8mo agoembedCompatibility with all xgboost versions
- 10mo agorstanarmrstanarm 2.32.2 migrates formula machinery to reformulas
- 11mo agoembedstep_lencode() adds analytical likelihood encoding with pooling
- 1y agoembedUMAP initial and target_weight become tunable
- 2y agoembedkeras and tensorflow moved to Suggests
- 2y agorstanarmrstanarm 2.32.1 fixes unit_vector error, enables LTO
- 2y agoembedstep_collapse_stringdist() returns factors
- 2y agorstanarmrstanarm 2.26.1 adopts new rstan syntax and as_draws()
- 4y agorstanarmrstanarm 2.21.3 fixes loo() and adds stan_jm offsets
- 6y agorstanarmrstanarm 2.21.1 changes default prior behaviour
Frequently asked questions
What is the difference between embed and rstanarm?
They serve adjacent needs but don't currently overlap on shipped themes. embed and rstanarm 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 embed better than rstanarm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. embed and rstanarm 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 embed?
Top embed alternatives in Analytics are ranked by recent ship velocity. Browse the "embed alternatives" section above for the current picks, or visit /alternatives/embed for the full list with editorial commentary on each.
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.