fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
Comparison · Analytics
bayestools vs detectseparation
A side-by-side editorial comparison of bayestools and detectseparation — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bayestools vs detectseparation: at a glance
What is bayestools?
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
What is detectseparation?
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.
bayestools vs detectseparation: editorial side-by-side
bayestools
0.0ANALYTICS
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
◆ Current state
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
◆ Where it's heading
This package's releases are best read against what depends on them. The 0.2.x fixes track features appearing in RoBMA one version later, and 0.3.0 landed a single day before RoBMA 4.0.0 — the standardization and sample-transformation functions are the substrate that rewrite needed. The direction of the work is toward sensible defaults: default priors by predictor type, automatic standardization for sampling stability, and transformation back to interpretable scale so the convenience does not cost the user their units.
◆ Prediction
Given how tightly its releases track downstream needs, the next version is most likely driven by gaps surfacing in RoBMA 4.0.x rather than by independent feature work.
detectseparation
0.0ANALYTICS
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to bayestools and detectseparation
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 bayestools or detectseparation.
gcube
gcube's recent releases are all packaging metadata, not simulation code
cubist
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats
ggstats keeps widening what a coefficient or Likert plot can be
ecodive
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
simStateSpace
State-space data simulation for R, filled in one function at a time
See all bayestools alternatives → · See all detectseparation alternatives →
Recent activity from bayestools and detectseparation
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agobayestoolsAdds automatic predictor standardization and type-based default priors
- 3mo agodetectseparationdetectseparation v0.4
- 8mo agobayestoolsBayesTools 0.2.23
- 8mo agobayestoolsBayesTools 0.2.22
- 11mo agobayestoolsBayesTools 0.2.21
- 1y agobayestoolsBayesTools 0.2.20
- 1y agobayestoolsBayesTools 0.2.19
- 3y agodetectseparationdetectseparation v0.3
- 5y agodetectseparationdetectseparation v0.2
Frequently asked questions
What is the difference between bayestools and detectseparation?
Both compete on the same themes — r-package — within Analytics. bayestools and detectseparation 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 bayestools better than detectseparation?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestools and detectseparation 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 bayestools?
Top bayestools alternatives in Analytics are ranked by recent ship velocity. Browse the "bayestools alternatives" section above for the current picks, or visit /alternatives/bayestools for the full list with editorial commentary on each.
What are the best alternatives to detectseparation?
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.