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collapse vs hdnom

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

collapse vs hdnom: at a glance

Featurecollapsehdnom
SectorAnalyticsAnalytics
Velocity score0.05.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticssurvival analysis, r, regularization, nomograms
Last editorial update1h ago3h 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 hdnom?

hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to

hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.

Read the full hdnom trajectory →

collapse vs hdnom: 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
hdnom
ANALYTICS
5.0

hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to

◆ Current state

hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.

◆ Where it's heading

The releases track two upstream pressures with no feature work of its own. glmnet is the larger one: its 4.1-9 change to how Cox cross-validation errors are normalized made lambda.1se select null models far more often, forcing hdnom to expose a rule argument and switch its examples to lambda.min. R-devel is the other, producing a steady trickle of strict-headers, deprecated-symbol and check-note fixes. The pattern is consistent — absorb the upstream change, default to whatever preserves existing behaviour, let users opt into the new one.

◆ Prediction

The cox.ties default is explicitly pinned to "breslow" to silence glmnet's migration warning, which is a deferral rather than a decision; expect a future release to flip that default to "efron" once glmnet completes the transition.

Alternatives to collapse and hdnom

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 hdnom.

See all collapse alternatives → · See all hdnom alternatives →

Recent activity from collapse and hdnom

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

  1. 18d agohdnomhdnom 6.2.1
  2. 18d agohdnomhdnom 6.2.0 pins Cox tie handling ahead of glmnet's migration
  3. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  4. 7mo agocollapseNegative zero now hashes equal to zero across the package
  5. 8mo agocollapsecollap() no longer double-aggregates external weights
  6. 9mo agocollapseCustom unlist() preserves attributes
  7. 0y agocollapseAssorted bug fixes
  8. 1y agohdnomhdnom 6.1.0 exposes lambda selection after a glmnet normalization change
  9. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  10. 1y agohdnomhdnom 6.0.4
  11. 2y agohdnomhdnom 6.0.3
  12. 3y agohdnomhdnom 6.0.2

Frequently asked questions

What is the difference between collapse and hdnom?

They serve adjacent needs but don't currently overlap on shipped themes. hdnom is currently shipping more aggressively (velocity 5.0 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 hdnom?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hdnom is currently shipping more aggressively (velocity 5.0 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 hdnom?

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