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collapse vs distributions3

A side-by-side editorial comparison of collapse and distributions3 — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

collapse vs distributions3: at a glance

Featurecollapsedistributions3
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsr-package, probability-distributions, statistical-modelling, maintainership
Last editorial update1h ago49m ago
WebsiteVisit →Visit →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

What is distributions3?

distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.

An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.

Read the full distributions3 trajectory →

collapse vs distributions3: editorial side-by-side

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

D2.5

distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.

◆ Current state

An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.

◆ Where it's heading

The package's growth has come in two modes. Early releases absorbed whole families of distributions from outside contributors — the extreme-value set, Erlang, later the Poisson binomial — while later ones tightened the interface itself with is_discrete() and is_continuous() generics and elementwise type-safety when applying a distribution vector to a numeric vector. The handover is the notable event in the current window: maintenance moves to the author of the surrounding statistical ecosystem this package already integrates with through prodist() and countreg, which suggests the interface work will continue over the distribution-collection work.

◆ Prediction

Expect closer alignment with Zeileis's own packages, with prodist() coverage widening to more model classes; the entries here do not indicate whether new distribution families remain on the agenda.

Alternatives to collapse and distributions3

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 collapse or distributions3.

See all collapse alternatives → · See all distributions3 alternatives →

Recent activity from collapse and distributions3

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

  1. 24d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
  2. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  3. 7mo agocollapseNegative zero now hashes equal to zero across the package
  4. 8mo agocollapsecollap() no longer double-aggregates external weights
  5. 9mo agocollapseCustom unlist() preserves attributes
  6. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  7. 0y agocollapseAssorted bug fixes
  8. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  9. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  10. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  11. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic

Frequently asked questions

What is the difference between collapse and distributions3?

Both compete on the same themes — r-package — within Analytics. distributions3 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 collapse better than distributions3?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 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 collapse?

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

What are the best alternatives to distributions3?

Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.