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collapse vs hstats

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

collapse vs hstats: at a glance

Featurecollapsehstats
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsinteraction statistics, partial dependence, model explainability, r package
Last editorial update1h ago4h 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 hstats?

hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.

hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.

Read the full hstats trajectory →

collapse vs hstats: 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.

H
hstats
ANALYTICS
0.0

hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.

◆ Current state

hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.

◆ Where it's heading

The structural work — the hstats_matrix object, quantile approximation, revised plotting — landed in 1.0.0 just outside this window, and nothing since has changed the package's shape. What continues is model-coverage plumbing: mlr3 classification modes, ranger survival behind a survival argument, and factor predictions added in 1.1.0 then removed again in 1.2.0. The most recent releases are compatibility-driven, tracking ggplot2 rather than the interaction statistics.

◆ Prediction

Expect the next release to be another dependency-compatibility pass or a new model backend working out of the box, rather than new interaction statistics.

Alternatives to collapse and hstats

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 hstats.

See all collapse alternatives → · See all hstats alternatives →

Recent activity from collapse and hstats

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

  1. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  2. 7mo agocollapseNegative zero now hashes equal to zero across the package
  3. 8mo agocollapsecollap() no longer double-aggregates external weights
  4. 9mo agocollapseCustom unlist() preserves attributes
  5. 10mo agohstatsggplot 4.0 compatibility and test coverage
  6. 0y agocollapseAssorted bug fixes
  7. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  8. 1y agohstatsranger survival models supported out of the box
  9. 2y agohstatsMoves to ModelOriented; factor predictions removed
  10. 2y agohstatsICE facets for multioutput models; mlr3 fixes
  11. 2y agohstatsFaster data.frame paths; NaN H-statistics fixed
  12. 2y agohstatsFactor predictions and line-style 2D partial dependence

Frequently asked questions

What is the difference between collapse and hstats?

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

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

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