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detectseparation vs fastglm

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

Shared themes:r-package

detectseparation vs fastglm: at a glance

Featuredetectseparationfastglm
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, regression, diagnostics, separationstatistical-computing, generalized-linear-models, cpp, r-package
Last editorial update57m ago2h ago
WebsiteVisit →Visit →

What is detectseparation?

A diagnostic package that generalized past its own name, then learned to say which kind of separation it found

detectseparation identifies separation and infinite estimates in binomial-response GLMs — the condition where maximum likelihood estimates diverge and standard software reports large coefficients with enormous standard errors instead of an error. Version 0.3 was the structural turn: detect_infinite_estimates() became the general method covering log, logit, probit and cauchit links, with detect_separation() demoted to a wrapper around it. Version 0.4 in April 2026 adds the ability to distinguish complete from quasi-complete separation via separation_type.

Read the full detectseparation trajectory →

What is fastglm?

A fast GLM solver stops being one function and becomes a count-model family

fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.

Read the full fastglm trajectory →

detectseparation vs fastglm: editorial side-by-side

D0.0

A diagnostic package that generalized past its own name, then learned to say which kind of separation it found

◆ Current state

detectseparation identifies separation and infinite estimates in binomial-response GLMs — the condition where maximum likelihood estimates diverge and standard software reports large coefficients with enormous standard errors instead of an error. Version 0.3 was the structural turn: detect_infinite_estimates() became the general method covering log, logit, probit and cauchit links, with detect_separation() demoted to a wrapper around it. Version 0.4 in April 2026 adds the ability to distinguish complete from quasi-complete separation via separation_type.

◆ Where it's heading

The package has been generalizing steadily — first past its own framing, since separation is one case of infinite estimates rather than the whole problem, and now toward finer classification of what it detects. The distinction 0.4 adds is practically useful because complete and quasi-complete separation call for different responses. Release intervals are long, roughly two to four years, which fits a diagnostic tool whose underlying theory is settled.

◆ Prediction

With link coverage broad and separation now classified by type, further work is more likely to refine reporting than to extend detection to new model families.

F
fastglm
ANALYTICS
0.0

A fast GLM solver stops being one function and becomes a count-model family

◆ Current state

fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.

◆ Where it's heading

The package changed what it is. Through 0.0.3 it was a drop-in replacement for glm() competing on speed; from 0.1.0 it targets the models people leave base R for — MASS::glm.nb, pscl::hurdle, pscl::zeroinfl — and reimplements their full estimation loops natively. The 0.1.1 follow-up is consolidation on that new surface: Firth generalised past binomial logit, SQUAREM acceleration on the zero-inflation EM driver, and a run of clamping guards and initialization fixes on the families most prone to overflow.

◆ Prediction

The numerical-stability work in 0.1.1 clusters on Tweedie and the inverse and sqrt link families, which suggests those paths are the newest and least exercised — expect further correctness fixes there before new model types.

Alternatives to detectseparation and fastglm

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 detectseparation or fastglm.

See all detectseparation alternatives → · See all fastglm alternatives →

Recent activity from detectseparation and fastglm

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

  1. 2mo agofastglmFirth generalised to all families, plus SQUAREM and stability fixes
  2. 3mo agofastglmCRAN release 0.1.0
  3. 3mo agodetectseparationdetectseparation v0.4
  4. 3y agodetectseparationdetectseparation v0.3
  5. 4y agofastglmC++ headers exposed for linking
  6. 5y agodetectseparationdetectseparation v0.2
  7. 7y agofastglmFirst CRAN release of the C++ IRLS solver

Frequently asked questions

What is the difference between detectseparation and fastglm?

Both compete on the same themes — r-package — within Analytics. detectseparation and fastglm 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 detectseparation better than fastglm?

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

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

What are the best alternatives to fastglm?

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