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Comparison · Analytics
fastglm vs qualpalr
A side-by-side editorial comparison of fastglm and qualpalr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fastglm vs qualpalr: at a glance
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.
What is qualpalr?
A palette generator became a palette platform — and changed the metric behind every color it picks.
qualpalr generates maximally distinct categorical color palettes by optimizing perceptual distance, with adaptation for color vision deficiency built in from early on. Version 1.0.0 in August 2025 ended an eight-year stretch of small maintenance releases: the color-difference metric became selectable, existing palettes from ColorBrewer and Tableau became usable as input, and functions arrived to list, retrieve, extend and analyze palettes rather than only generate them. The C++ backend was rewritten as part of the same release.
fastglm vs qualpalr: editorial side-by-side
fastglm
0.0ANALYTICS
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.
qualpalr
0.0ANALYTICS
A palette generator became a palette platform — and changed the metric behind every color it picks.
◆ Current state
qualpalr generates maximally distinct categorical color palettes by optimizing perceptual distance, with adaptation for color vision deficiency built in from early on. Version 1.0.0 in August 2025 ended an eight-year stretch of small maintenance releases: the color-difference metric became selectable, existing palettes from ColorBrewer and Tableau became usable as input, and functions arrived to list, retrieve, extend and analyze palettes rather than only generate them. The C++ backend was rewritten as part of the same release.
◆ Where it's heading
The package is moving from a generator to a toolkit that also works on palettes it did not create. Accepting a named palette as input, extending an existing one, and analyzing an arbitrary categorical palette all point the optimization machinery outward at the palettes people already use. The color-vision-deficiency handling followed the same path, consolidating from a single cvd_severity scalar to a named vector giving protan, deuter and tritan their own severities.
◆ Prediction
Two deprecations are explicitly staged for the next major release — autopal(), with no replacement offered, and cvd_severity — so removal is the most likely next structural step. The 1.0.1 release already tracks the underlying qualpal C++ library separately, suggesting future changes may arrive from there.
Alternatives to fastglm and qualpalr
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 qualpalr.
cfbfastr
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The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
rempsyc
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
sdsfun
A spatial-statistics utility package exists to be depended on, and is built accordingly.
See all fastglm alternatives → · See all qualpalr alternatives →
Recent activity from fastglm and qualpalr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agofastglmFirth generalised to all families, plus SQUAREM and stability fixes
- 3mo agofastglmCRAN release 0.1.0 ⚡
- 10mo agoqualpalrJOSS citation added and C++ library bumped to 3.3.0
- 0y agoqualpalrSelectable difference metric, palette input, and a rewritten backend ⚡
- 2y agoqualpalrRcppParallel dropped and n_threads deprecated
- 4y agofastglmC++ headers exposed for linking
- 7y agofastglmFirst CRAN release of the C++ IRLS solver
- 7y agoqualpalrThreaded distance-matrix computation via a new n_threads argument
- 8y agoqualpalrPalette generation becomes deterministic
- 9y agoqualpalrautopal() fixed after a zero-difference bug
Frequently asked questions
What is the difference between fastglm and qualpalr?
Both compete on the same themes — r-package — within Analytics. fastglm and qualpalr 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 qualpalr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastglm and qualpalr 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 qualpalr?
Top qualpalr alternatives in Analytics are ranked by recent ship velocity. Browse the "qualpalr alternatives" section above for the current picks, or visit /alternatives/qualpalr for the full list with editorial commentary on each.