gcube
gcube's recent releases are all packaging metadata, not simulation code
Comparison · Analytics
bayestools vs fillpattern
A side-by-side editorial comparison of bayestools and fillpattern — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bayestools vs fillpattern: 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 fillpattern?
Pattern fills for ggplot2, hardened against the ways users write sizes
fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.
bayestools vs fillpattern: 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.
fillpattern
0.0ANALYTICS
Pattern fills for ggplot2, hardened against the ways users write sizes
◆ Current state
fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.
◆ Where it's heading
Development is slow and entirely reactive to how the string-based size interface fails. The pattern across releases is the same: a user hits an edge — very small fill areas in 1.0.2, malformed unit strings in 1.0.3 — and the fix is either a graceful fallback or a clearer error. Leaning on R's newer graphics engine rather than reimplementing pattern rendering keeps the package small at the cost of raising its version floor.
◆ Prediction
Expect further releases to stay in the same register: parsing and validation fixes for the size and unit interface, with the pattern set itself unlikely to change.
Alternatives to bayestools and fillpattern
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 fillpattern.
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
rollama
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
See all bayestools alternatives → · See all fillpattern alternatives →
Recent activity from bayestools and fillpattern
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agobayestoolsAdds automatic predictor standardization and type-based default priors
- 6mo agofillpatternSize string parsing fixed; invalid units now report instead of crash
- 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
- 2y agofillpatternSmall fill areas no longer crash; min_size falls back to solid
- 2y agofillpatternfillpattern 1.0.1
Frequently asked questions
What is the difference between bayestools and fillpattern?
Both compete on the same themes — r-package — within Analytics. bayestools and fillpattern 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 fillpattern?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestools and fillpattern 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 fillpattern?
Top fillpattern alternatives in Analytics are ranked by recent ship velocity. Browse the "fillpattern alternatives" section above for the current picks, or visit /alternatives/fillpattern for the full list with editorial commentary on each.