simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of fastglm and stringx — 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.
A drop-in string API for base R, kept alive by upstream check failures.
stringx reimplements base R's string and date-time functions on top of stringi, aiming for consistent and Unicode-correct behaviour. The visible window holds one behavioural change and five releases that exist because R or stringi moved underneath it. None of the recent notes add capability.
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.
stringx reimplements base R's string and date-time functions on top of stringi, aiming for consistent and Unicode-correct behaviour. The visible window holds one behavioural change and five releases that exist because R or stringi moved underneath it. None of the recent notes add capability.
The package's shape was settled by 0.2.1 and has not changed since; every release in the past three years is either a check failure fixed or a POSIXxt defect. The one substantive note, 0.2.6, records a behaviour change inherited from stringi rather than chosen here - strptime now fills missing fields from today's midnight. That dependence is the defining fact about the feed.
The next release is most likely another compatibility fix timed to an R or stringi update, since four of the six visible releases were exactly that.
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 stringx.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
From a bundled hospital dataset to a live CMS API client.
See all fastglm alternatives → · See all stringx alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. fastglm and stringx 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 stringx 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 stringx alternatives in Analytics are ranked by recent ship velocity. Browse the "stringx alternatives" section above for the current picks, or visit /alternatives/stringx for the full list with editorial commentary on each.