tEDM
The temporal half of the stscl EDM pair, tracking its spatial sibling
Comparison · Analytics
brglm2 vs dissmapr
A side-by-side editorial comparison of brglm2 and dissmapr — release velocity, themes, recent moves, and the top alternatives to consider.
brglm2 vs dissmapr: 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 dissmapr?
dissmapr spent its first releases becoming citable rather than adding methods.
dissmapr provides an R workflow for compositional dissimilarity and turnover — occurrence data through spatial gridding and environmental linkage to order-wise dissimilarity and bioregional mapping. All three releases to date are infrastructure: a first citable archive in June 2026, then a maturity release aligning the package with the B-Cubed software development guide. The ten-function pipeline described in the notes has not changed across them.
brglm2 vs dissmapr: 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.
dissmapr
0.0ANALYTICS
dissmapr spent its first releases becoming citable rather than adding methods.
◆ Current state
dissmapr provides an R workflow for compositional dissimilarity and turnover — occurrence data through spatial gridding and environmental linkage to order-wise dissimilarity and bioregional mapping. All three releases to date are infrastructure: a first citable archive in June 2026, then a maturity release aligning the package with the B-Cubed software development guide. The ten-function pipeline described in the notes has not changed across them.
◆ Where it's heading
The work is compliance-shaped rather than method-shaped: explicit @importFrom in place of whole-namespace imports, library() calls removed from package code, roughly 11 MB of development caches dropped, a runnable README quick-start, and Zenodo archival with CITATION.cff and codemeta.json. dissmapr moves in lockstep with its B-Cubed sibling invasimapr — both tagged 0.1.0 within three minutes of each other and 0.2.0 on the same day — so releases here reflect project-wide standards deadlines more than package-specific work. The stated roadmap of additional ecological distance metrics has not yet landed.
◆ Prediction
With standards work now signed off and R CMD check clean, the next release is the first real chance for the roadmap items — additional ecological distance metrics — to arrive.
Alternatives to brglm2 and dissmapr
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 dissmapr.
spEDM
Spatial causal discovery in R, one exposed method per release
sccore
Shared plumbing for the Kharchenko single-cell stack, updated once a year
rdataone
The R client for DataONE ships slow, correctness-focused maintenance
tall
A Shiny text-mining GUI grows into a full NLP workbench at 1.0.0
nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
See all brglm2 alternatives → · See all dissmapr alternatives →
Recent activity from brglm2 and dissmapr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodissmaprVersion bump; notes identical to 0.2.0
- 1mo agodissmaprB-Cubed standards alignment, docs overhaul and a citable DOI
- 1mo agodissmaprdissmapr v0.1.0: First citable release
- 3mo agobrglm2brglm2 v1.1.0
- 8mo agobrglm2brglm2 v1.0.1
- 11mo agobrglm21.0.0 adds maximum DY-prior penalized likelihood for logistic regression ⚡
- 1y agobrglm2brglm2 v0.9.3
- 1y agobrglm2brglm2 v0.9.2
- 3y agobrglm2brglm2 v0.9.1
Frequently asked questions
What is the difference between brglm2 and dissmapr?
They serve adjacent needs but don't currently overlap on shipped themes. brglm2 and dissmapr 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 dissmapr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. brglm2 and dissmapr 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 dissmapr?
Top dissmapr alternatives in Analytics are ranked by recent ship velocity. Browse the "dissmapr alternatives" section above for the current picks, or visit /alternatives/dissmapr for the full list with editorial commentary on each.