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fastglm vs kde1d

A side-by-side editorial comparison of fastglm and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

fastglm vs kde1d: at a glance

Featurefastglmkde1d
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstatistical-computing, generalized-linear-models, cpp, r-packagedensity-estimation, kernel-methods, zero-inflation, cpp-library
Last editorial update7h ago1h ago
WebsiteVisit →Visit →

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 →

What is kde1d?

A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.

kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.

Read the full kde1d trajectory →

fastglm vs kde1d: editorial side-by-side

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.

K
kde1d
ANALYTICS
0.0

A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.

◆ Current state

kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.

◆ Where it's heading

The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.

◆ Prediction

With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.

Alternatives to fastglm and kde1d

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 fastglm or kde1d.

See all fastglm alternatives → · See all kde1d alternatives →

Recent activity from fastglm and kde1d

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. 1y agokde1dkde1d 1.1.1
  4. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  5. 4y agofastglmC++ headers exposed for linking
  6. 4y agokde1dBit-wise Boolean operations removed
  7. 5y agokde1ddkde1d() invisible output fixed
  8. 5y agokde1dValgrind false positive silenced
  9. 6y agokde1dqrng dependency dropped; undefined behaviour fixed
  10. 7y agofastglmFirst CRAN release of the C++ IRLS solver

Frequently asked questions

What is the difference between fastglm and kde1d?

Both compete on the same themes — r-package — within Analytics. fastglm and kde1d 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 fastglm better than kde1d?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastglm and kde1d 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 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.

What are the best alternatives to kde1d?

Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.