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collapse vs RadialMR

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

Shared themes:r-package

collapse vs RadialMR: at a glance

FeaturecollapseRadialMR
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsmendelian-randomization, radial-plots, correctness-audit, statistical-inference
Last editorial update1h ago1h 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 RadialMR?

RadialMR's 2026 release corrects degrees of freedom that had been wrong since documentation.

RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().

Read the full RadialMR trajectory →

collapse vs RadialMR: 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.

R
RadialMR
ANALYTICS
0.0

RadialMR's 2026 release corrects degrees of freedom that had been wrong since documentation.

◆ Current state

RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().

◆ Where it's heading

This is a package being read closely by its maintainer rather than extended. The 1.2.x line pairs statistical corrections with defensive hardening — an rmr_format class check so unformatted input fails with a clear message, and plotly_radial() dispatching on object class instead of counting list elements. Both are the kind of change made while auditing, not while building.

◆ Prediction

Expect the audit to continue into the remaining estimator internals and print methods rather than new radial variants; the entries show no feature work queued.

Alternatives to collapse and RadialMR

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 RadialMR.

See all collapse alternatives → · See all RadialMR alternatives →

Recent activity from collapse and RadialMR

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

  1. 1mo agoRadialMRegger_radial() degrees of freedom corrected to n-2
  2. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  3. 3mo agoRadialMRroxygen2 bumped; package-level helpfile added
  4. 4mo agoRadialMRUnspecified codebase optimizations
  5. 7mo agocollapseNegative zero now hashes equal to zero across the package
  6. 8mo agocollapsecollap() no longer double-aggregates external weights
  7. 9mo agocollapseCustom unlist() preserves attributes
  8. 0y agocollapseAssorted bug fixes
  9. 1y agoRadialMRggplot2 v4 warning removed from plot_radial()
  10. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up

Frequently asked questions

What is the difference between collapse and RadialMR?

Both compete on the same themes — r-package — within Analytics. collapse and RadialMR 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 RadialMR?

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

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