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fastglm vs piecepackr

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

Shared themes:r-package

fastglm vs piecepackr: at a glance

Featurefastglmpiecepackr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstatistical-computing, generalized-linear-models, cpp, r-packageboard-games, graphics, r-package, 3d-rendering
Last editorial update2h 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 piecepackr?

A board game graphics package runs one of the most disciplined deprecation cycles in R.

piecepackr renders game pieces — piecepack, chess, dominoes and related systems — as 2D grid graphics, 3D meshes, animations, and print-and-play PDFs. Its interface is mature enough that most releases are about managing change rather than adding capability: features get deprecated with a named replacement, live through a release or two, then get removed on schedule. The current release completes the cycle opened a year earlier, retiring the new_device and style arguments in favour of open_device and the composable font, border, background_color and edge_color set.

Read the full piecepackr trajectory →

fastglm vs piecepackr: 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.

P
piecepackr
ANALYTICS
0.0

A board game graphics package runs one of the most disciplined deprecation cycles in R.

◆ Current state

piecepackr renders game pieces — piecepack, chess, dominoes and related systems — as 2D grid graphics, 3D meshes, animations, and print-and-play PDFs. Its interface is mature enough that most releases are about managing change rather than adding capability: features get deprecated with a named replacement, live through a release or two, then get removed on schedule. The current release completes the cycle opened a year earlier, retiring the new_device and style arguments in favour of open_device and the composable font, border, background_color and edge_color set.

◆ Where it's heading

Two things dominate the log. The first is that deprecation discipline, unusually explicit for a package this size — every removal names its successor, and deprecations announced in one release are removed in a predictable later one. The second is defensive dependency management: version bumps pinned around bugs introduced upstream in rayrender and rayvertex, a warning class for known-buggy cairo versions with an option to suppress it, and suggested packages required for metadata embedding with clear messages when they are absent. Functionality still arrives — vectorised 3D object export that finally handles composite pieces, new crosshair grobs, a reworked colour palette — but it arrives inside that maintenance rhythm rather than driving it.

◆ Prediction

The features deprecated in this release — the preview_layout component and the 4x6 print-and-play size — are on the established path toward removal in a future version, with the documented ppdf-based replacement already in place.

Alternatives to fastglm and piecepackr

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 piecepackr.

See all fastglm alternatives → · See all piecepackr alternatives →

Recent activity from fastglm and piecepackr

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

  1. 2mo agofastglmFirth generalised to all families, plus SQUAREM and stability fixes
  2. 3mo agopiecepackrYear-old deprecations removed; new crosshair grobs added
  3. 3mo agofastglmCRAN release 0.1.0
  4. 10mo agopiecepackrExamples updated off the deprecated style argument
  5. 1y agopiecepackrSuit colours redrawn and piece styling made composable
  6. 1y agopiecepackr3D export vectorised, and composite pieces stop erroring
  7. 1y agopiecepackrrayrender pinned around an upstream bug
  8. 2y agopiecepackrrayvertex pinned around an upstream mesh bug
  9. 4y agofastglmC++ headers exposed for linking
  10. 7y agofastglmFirst CRAN release of the C++ IRLS solver

Frequently asked questions

What is the difference between fastglm and piecepackr?

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

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

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