fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of brglm2 and rdataone — release velocity, themes, recent moves, and the top alternatives to consider.
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.
The R client for DataONE ships slow, correctness-focused maintenance
rdataone is the R client for the DataONE federated research-data network, handling authentication, upload and retrieval of data packages against member nodes. Recent work is concentrated on correctness in the upload path — rightsHolder persistence, public-read flags applied across all objects in a package, and edge cases in archive() — plus dependency trimming. The feed's version stamps are unreliable: 2.2.2 carries a later publication date than 2.3.0, which cites 2.2.2 as its own predecessor.
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.
rdataone is the R client for the DataONE federated research-data network, handling authentication, upload and retrieval of data packages against member nodes. Recent work is concentrated on correctness in the upload path — rightsHolder persistence, public-read flags applied across all objects in a package, and edge cases in archive() — plus dependency trimming. The feed's version stamps are unreliable: 2.2.2 carries a later publication date than 2.3.0, which cites 2.2.2 as its own predecessor.
This is long-cycle infrastructure maintenance, not feature development. Release intervals run to years, and the content is dominated by access-control correctness, CRAN compliance and TLS/platform fixes rather than new client capability. The one consistent thread is hardening how permissions and checksums survive a round trip to a member node.
Expect continued low-frequency releases driven by CRAN check failures and platform TLS changes, with any functional work staying in the upload and permissions path rather than the query surface.
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 brglm2 or rdataone.
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 brglm2 alternatives → · See all rdataone alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. brglm2 and rdataone 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. brglm2 and rdataone 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 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.
Top rdataone alternatives in Analytics are ranked by recent ship velocity. Browse the "rdataone alternatives" section above for the current picks, or visit /alternatives/rdataone for the full list with editorial commentary on each.