ggstats
ggstats keeps widening what a coefficient or Likert plot can be
A side-by-side editorial comparison of detectseparation and glmbayes — release velocity, themes, recent moves, and the top alternatives to consider.
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
detectseparation identifies separation and infinite estimates in binomial-response GLMs — the condition where maximum likelihood estimates diverge and standard software reports large coefficients with enormous standard errors instead of an error. Version 0.3 was the structural turn: detect_infinite_estimates() became the general method covering log, logit, probit and cauchit links, with detect_separation() demoted to a wrapper around it. Version 0.4 in April 2026 adds the ability to distinguish complete from quasi-complete separation via separation_type.
A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain
glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.
detectseparation identifies separation and infinite estimates in binomial-response GLMs — the condition where maximum likelihood estimates diverge and standard software reports large coefficients with enormous standard errors instead of an error. Version 0.3 was the structural turn: detect_infinite_estimates() became the general method covering log, logit, probit and cauchit links, with detect_separation() demoted to a wrapper around it. Version 0.4 in April 2026 adds the ability to distinguish complete from quasi-complete separation via separation_type.
The package has been generalizing steadily — first past its own framing, since separation is one case of infinite estimates rather than the whole problem, and now toward finer classification of what it detects. The distinction 0.4 adds is practically useful because complete and quasi-complete separation call for different responses. Release intervals are long, roughly two to four years, which fits a diagnostic tool whose underlying theory is settled.
With link coverage broad and separation now classified by type, further work is more likely to refine reporting than to extend detection to new model families.
glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.
The arc is about removing reasons not to use it. GPU support was previously blocked on Windows because the OpenCL kernels were vendored; splitting them into a CRAN package with binaries fixed that. The ecosystem work does the same thing for tooling — a glmb fit now responds to get_parameters, get_priors, simulate_prior and check_prior, so it drops into workflows built around easystats rather than requiring its own. The CRAN archival and the configure fixes that followed show how much of the effort goes into distribution rather than modelling.
get_priors() returning the full prior specification rather than a marginal table is the kind of detail that invites further bayestestR integration, and the diagnostic surface is the least built-out part of what has shipped so far.
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 detectseparation or glmbayes.
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
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
A ggplot2 inset-map extension that is now infrastructure for other packages
hoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems
See all detectseparation alternatives → · See all glmbayes alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. glmbayes is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. 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. glmbayes is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top detectseparation alternatives in Analytics are ranked by recent ship velocity. Browse the "detectseparation alternatives" section above for the current picks, or visit /alternatives/detectseparation for the full list with editorial commentary on each.
Top glmbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "glmbayes alternatives" section above for the current picks, or visit /alternatives/glmbayes for the full list with editorial commentary on each.