fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of fastglm and nswgeo — release velocity, themes, recent moves, and the top alternatives to consider.
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.
NSW boundary data for R, refreshed as the official sources move
nswgeo packages New South Wales geographic boundaries for R — suburbs, postcodes, local government areas, Primary Health Networks and Local Health Districts — as ready-to-plot sf datasets. The 0.6.0 release refreshes nearly all of them against new upstream sources, moving postcodes to 2021 ABS boundaries and taking LHD boundaries from a new official feed. It is maintained by cidm-ph alongside the mapping packages that consume it, including ggmapinset.
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.
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.
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.
nswgeo packages New South Wales geographic boundaries for R — suburbs, postcodes, local government areas, Primary Health Networks and Local Health Districts — as ready-to-plot sf datasets. The 0.6.0 release refreshes nearly all of them against new upstream sources, moving postcodes to 2021 ABS boundaries and taking LHD boundaries from a new official feed. It is maintained by cidm-ph alongside the mapping packages that consume it, including ggmapinset.
Every release is dictated by an upstream release calendar rather than a roadmap: the 2023 ASGS, then 2024, then the 2021 ABS postcode boundaries and the new LHD source. That makes field-name churn the package's defining hazard — LGA_NAME_2021 to LGA_NAME_2023 to LGA_NAME_2024, and now lhd_name carrying a Local Health District suffix. The maintainer's habit of registering compatibility aliases through cartographer shows an awareness that these renames break downstream code silently.
Expect the next release to track the following ASGS edition with another round of field renames, and any new content to stay in the health-geography area the package's users work in.
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 nswgeo.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
State-space data simulation for R, filled in one function at a time
See all fastglm alternatives → · See all nswgeo alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. fastglm and nswgeo 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastglm and nswgeo 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.
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.
Top nswgeo alternatives in Analytics are ranked by recent ship velocity. Browse the "nswgeo alternatives" section above for the current picks, or visit /alternatives/nswgeo for the full list with editorial commentary on each.