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Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of antaresread and brglm2 — release velocity, themes, recent moves, and the top alternatives to consider.
The R reader for Antares Simulator studies, pinned to whatever the simulator ships next
antaresRead loads Antares Simulator studies from disk or the Antares Web API into R. Its release history maps one-to-one onto simulator versions: 2.9.2 for Antares 9.2, 2.9.3 for 9.3, and the 3.0.x line for the study-format changes that followed. The recurring work is the converted study version format (9.0 becoming 900) which has now been fixed or re-fixed in three consecutive releases, and 3.1.0 turns that churn into a declared breaking change as Antares Web 2.33.0 introduces yet another numbering scheme.
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
brglm2 fits generalized linear models using mean and median bias reduction rather than plain maximum likelihood, which matters most when ML estimates are infinite or badly biased. The 0.7-0.9 line broadened coverage — negative binomial via brnb(), ordinal superiority measures, the expo() method for exponentiated parameters, add1()/drop1() so step() stops silently producing nonsense. Version 1.0.0 in August 2025 added mdyplFit(), estimating logistic regression by maximum Diaconis-Ylvisaker prior penalized likelihood with optional high-dimensional corrections. The two releases since have tuned that new path.
antaresRead loads Antares Simulator studies from disk or the Antares Web API into R. Its release history maps one-to-one onto simulator versions: 2.9.2 for Antares 9.2, 2.9.3 for 9.3, and the 3.0.x line for the study-format changes that followed. The recurring work is the converted study version format (9.0 becoming 900) which has now been fixed or re-fixed in three consecutive releases, and 3.1.0 turns that churn into a declared breaking change as Antares Web 2.33.0 introduces yet another numbering scheme.
The package is a compatibility layer whose roadmap is set entirely upstream, and version identity is where it keeps getting cut. The same .getSimOptionsAPI() version-format fix appears in 3.0.0, 3.0.1 and again in 3.1.0 — three passes at one problem, which suggests the API and disk representations of a study version have not converged. Alongside that, API-mode work is displacing disk-mode work: dedicated endpoints for output listing, district definitions, per-area output handling.
The next release will most likely track the following Antares Simulator or Antares Web version, and given the 3.1.0 breaking change, a follow-up correcting the new numbering scheme is a reasonable expectation.
brglm2 fits generalized linear models using mean and median bias reduction rather than plain maximum likelihood, which matters most when ML estimates are infinite or badly biased. The 0.7-0.9 line broadened coverage — negative binomial via brnb(), ordinal superiority measures, the expo() method for exponentiated parameters, add1()/drop1() so step() stops silently producing nonsense. Version 1.0.0 in August 2025 added mdyplFit(), estimating logistic regression by maximum Diaconis-Ylvisaker prior penalized likelihood with optional high-dimensional corrections. The two releases since have tuned that new path.
The package's older work assumed the classical regime where observations comfortably outnumber parameters. mdyplFit() and its hd_correction argument target the opposite case, and the follow-up releases are almost entirely about it — Pearson residuals on original responses, aliased parameter handling, the sloe() signal-strength estimator ignoring leverage-one observations. Meanwhile the older surface gets graceful-failure work: brglm_fit() now returns its latest estimates with warnings rather than aborting.
Given that 1.0.1 and 1.1.0 are both dominated by mdyplFit follow-ups while the classical path receives only robustness fixes, further work on high-dimensional corrections is the likeliest direction.
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 antaresread or brglm2.
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 antaresread alternatives → · See all brglm2 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. antaresread and brglm2 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. antaresread and brglm2 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 antaresread alternatives in Analytics are ranked by recent ship velocity. Browse the "antaresread alternatives" section above for the current picks, or visit /alternatives/antaresread for the full list with editorial commentary on each.
Top brglm2 alternatives in Analytics are ranked by recent ship velocity. Browse the "brglm2 alternatives" section above for the current picks, or visit /alternatives/brglm2 for the full list with editorial commentary on each.