nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
brglm2 vs slope
A side-by-side editorial comparison of brglm2 and slope — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
brglm2 vs slope: at a glance
What is brglm2?
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.
What is slope?
A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface
SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.
brglm2 vs slope: editorial side-by-side
brglm2
0.0ANALYTICS
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
slope
0.0ANALYTICS
A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface
◆ Current state
SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.
◆ Where it's heading
The arc runs rewrite, then repair, then convenience. The 1.2.0 release is the repair phase — coefficients_scaled was returning unscaled values, which silently affected every coef.SLOPE() call — and 2.0.0 onward is convenience, with refit() now working without re-supplying training data. The tag timestamps are non-monotonic: 1.0.1 is stamped a minute after 1.1.0 despite the lower version, so ordering here reflects when tags were pushed, not what superseded what.
◆ Prediction
With the cross-validation workflow now closing itself out through automatic refitting, further work is more likely to extend the summary and plotting surface than to touch the solver again.
Alternatives to brglm2 and slope
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 slope.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
robma
RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy
See all brglm2 alternatives → · See all slope alternatives →
Recent activity from brglm2 and slope
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agosloperefit() defaults to training data; class-mismatch scoring fixed
- 3mo agobrglm2brglm2 v1.1.0
- 6mo agoslopeCross-validation now refits automatically and gains summary methods
- 8mo agobrglm2brglm2 v1.0.1
- 9mo agoslopeSingle-threaded by default, interruptible, and a scaling bug fixed
- 9mo agoslopeM1 Mac test fix
- 9mo agoslopeGlioma gene expression dataset added
- 11mo agobrglm21.0.0 adds maximum DY-prior penalized likelihood for logistic regression ⚡
- 1y agobrglm2brglm2 v0.9.3
- 1y agobrglm2brglm2 v0.9.2
- 1y agoslopeSLOPE 1.0.0 ⚡
- 3y agobrglm2brglm2 v0.9.1
Frequently asked questions
What is the difference between brglm2 and slope?
Both compete on the same themes — r-package — within Analytics. brglm2 and slope 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 brglm2 better than slope?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. brglm2 and slope 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 brglm2?
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.
What are the best alternatives to slope?
Top slope alternatives in Analytics are ranked by recent ship velocity. Browse the "slope alternatives" section above for the current picks, or visit /alternatives/slope for the full list with editorial commentary on each.