fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of bayestools and condformat — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A dormant table-formatting package woken by a 20-PR correctness and coverage sweep
condformat applies conditional formatting rules to R data frames and renders them to HTML, LaTeX, Excel and grob output. After 0.10.1 in 2023 it went quiet for nearly three years. Version 0.11.0 breaks that silence with a single-maintainer sweep of roughly twenty pull requests: CI modernized across R-devel, release and oldrel; lockcells fixed for LaTeX and grob output; a rule_fill_bar() crash at zero width; theme_htmlTable() no longer dropping chained arguments; and a .col pronoun added across all rules.
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.
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.
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.
condformat applies conditional formatting rules to R data frames and renders them to HTML, LaTeX, Excel and grob output. After 0.10.1 in 2023 it went quiet for nearly three years. Version 0.11.0 breaks that silence with a single-maintainer sweep of roughly twenty pull requests: CI modernized across R-devel, release and oldrel; lockcells fixed for LaTeX and grob output; a rule_fill_bar() crash at zero width; theme_htmlTable() no longer dropping chained arguments; and a .col pronoun added across all rules.
This is a maintenance-debt payoff rather than a change of direction. The bulk of 0.11.0 is test coverage — render_gtable, knit_print, theme_grob, render_xlsx and rule_fill_bar all gained tests — which reads as a maintainer establishing a safety net before touching anything further. The .col pronoun and scalar recycling in the text rules are the only real API additions, and both smooth inconsistencies rather than extend the rule vocabulary.
With coverage and CI now in place, the next release is more likely to extend rule or output-format support than to continue with fixes, though the three-year gap makes cadence hard to call from these entries alone.
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 condformat.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
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
See all bayestools alternatives → · See all condformat alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. bayestools and condformat 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestools and condformat 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.
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.
Top condformat alternatives in Analytics are ranked by recent ship velocity. Browse the "condformat alternatives" section above for the current picks, or visit /alternatives/condformat for the full list with editorial commentary on each.