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posterior vs stacks

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

posterior vs stacks: at a glance

Featureposteriorstacks
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbayesian, rvar, pareto-diagnostics, r-infrastructuretidymodels, ensembling, parallel-processing, future-framework
Last editorial update58m ago1h ago
WebsiteVisit →Visit →

What is posterior?

posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.

The releases in this window advance on two fronts. The rvar random-variable type gained factor and ordered subtypes (1.4.0), rvar-indexed slicing and `rvar_ifelse()` (1.5.0), base `%*%` matrix multiplication and indexed variable names (1.6.0). Separately, Pareto diagnostics have grown from `pareto_smooth()` options and individual `pareto_khat()`-family functions (1.6.0) through `pit()` for draws and rvars (1.6.1) to exported generalized-Pareto functions and `pareto_pit` (1.7.0). 1.7.1 is a paperwork release for a JOSS submission.

Read the full posterior trajectory →

What is stacks?

Model stacking in tidymodels, quietly migrating off foreach and onto future

stacks builds ensembles from tidymodels tuning results, and its release history is dominated by one long project: replacing foreach-based parallelism with the future framework. That transition completed in 1.1.0, where foreach backends began being ignored with a warning and the minimum R version rose to 4.1. Releases are infrequent and small, with the most recent being a CRAN re-submission rather than a change.

Read the full stacks trajectory →

posterior vs stacks: editorial side-by-side

P
posterior
ANALYTICS
0.0

posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.

◆ Current state

The releases in this window advance on two fronts. The rvar random-variable type gained factor and ordered subtypes (1.4.0), rvar-indexed slicing and `rvar_ifelse()` (1.5.0), base `%*%` matrix multiplication and indexed variable names (1.6.0). Separately, Pareto diagnostics have grown from `pareto_smooth()` options and individual `pareto_khat()`-family functions (1.6.0) through `pit()` for draws and rvars (1.6.1) to exported generalized-Pareto functions and `pareto_pit` (1.7.0). 1.7.1 is a paperwork release for a JOSS submission.

◆ Where it's heading

posterior is positioning itself as shared infrastructure rather than an end-user package: 1.7.0 explicitly exports generalized-Pareto machinery 'for use in other packages', and the JOSS paper is a citation vehicle for the same audience. The rvar work points the same way — a random-variable type other Bayesian packages can build on. Cadence is steady but unhurried, roughly one feature release a year.

◆ Prediction

More diagnostic functions are likely to be exported for downstream reuse, following the pattern 1.7.0 established with the generalized-Pareto helpers.

S
stacks
ANALYTICS
0.0

Model stacking in tidymodels, quietly migrating off foreach and onto future

◆ Current state

stacks builds ensembles from tidymodels tuning results, and its release history is dominated by one long project: replacing foreach-based parallelism with the future framework. That transition completed in 1.1.0, where foreach backends began being ignored with a warning and the minimum R version rose to 4.1. Releases are infrequent and small, with the most recent being a CRAN re-submission rather than a change.

◆ Where it's heading

The package is mature and its remaining work is compatibility rather than capability — tracking the parallelism story across tidymodels, keeping object sizes sane after butchering and reloading, and staying aligned with recipes deprecations. The augment() method added for vetiver compatibility shows the same instinct: fit into the surrounding ecosystem rather than grow independently of it. Nothing in the visible history suggests new ensembling methods are being pursued.

◆ Prediction

With the future migration finished, the next release is most likely maintenance keeping pace with tune and recipes rather than anything users would notice.

Alternatives to posterior and stacks

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 posterior or stacks.

See all posterior alternatives → · See all stacks alternatives →

Recent activity from posterior and stacks

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

  1. 2mo agoposteriorposterior 1.7.1 released for JOSS paper
  2. 3mo agoposteriorposterior 1.7.0 exports generalized-Pareto functions
  3. 10mo agoposteriorposterior 1.6.1 adds pit() for draws and rvars
  4. 1y agostacksstacks 1.1.1 re-released to clear a CRAN check note
  5. 1y agostacksstacks 1.1.0 completes the move to future-based parallelism
  6. 1y agoposteriorposterior 1.6.0 adds Pareto diagnostics and ESS-based thinning
  7. 2y agostacksstacks 1.0.5 fixes butchered stack size inflation
  8. 2y agostacksstacks 1.0.4 introduces future-based parallel processing
  9. 2y agostacksstacks 1.0.3 clears recipes deprecations and a type-check bug
  10. 2y agoposteriorposterior 1.5.0 adds nested-Rhat and rvar indexing
  11. 3y agostacksstacks 1.0.2 adds an augment() method for vetiver compatibility
  12. 3y agoposteriorposterior 1.4.0 adds factor and ordered rvar subtypes

Frequently asked questions

What is the difference between posterior and stacks?

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

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. posterior and stacks 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 posterior?

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

What are the best alternatives to stacks?

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