randomwalk
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
A side-by-side editorial comparison of fillpattern and medrobust — release velocity, themes, recent moves, and the top alternatives to consider.
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.
medrobust made its partial-identification bounds usable by giving them confidence intervals.
medrobust computes partial-identification bounds for mediation effects when exposure or mediator is differentially misclassified, part of the Data-Wise mediationverse. Its 0.2.0 release corrected three estimator defects against population oracles and added Imbens-Manski confidence intervals for the bounds; the two releases since have paired each identification path with a real public-domain dataset and a worked vignette. CRAN is deferred, with distribution through GitHub and r-universe.
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.
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.
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.
medrobust computes partial-identification bounds for mediation effects when exposure or mediator is differentially misclassified, part of the Data-Wise mediationverse. Its 0.2.0 release corrected three estimator defects against population oracles and added Imbens-Manski confidence intervals for the bounds; the two releases since have paired each identification path with a real public-domain dataset and a worked vignette. CRAN is deferred, with distribution through GitHub and r-universe.
The pattern is deliberate and symmetric: 0.3.0 shipped the mediator-side example on NCHS natality data, 0.4.0 its exposure-side mirror on NHANES, each demonstrating what the bounds do when reporting accuracy is allowed to depend on the outcome. Alongside that runs a consistent concern with failing usefully rather than loudly — bound_ne() returns NA bounds with a machine-readable reason and a typed condition instead of aborting, so a simulation replicate is recorded rather than lost, and non-finite endpoint standard errors produce a documented NA rather than a silent one. That is a package expecting to be run thousands of times inside someone else's loop.
Both identification paths now have a dataset, a vignette and interval coverage, so the next release is most likely the deferred CRAN submission rather than new methodology.
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 fillpattern or medrobust.
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
See all fillpattern alternatives → · See all medrobust alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. fillpattern and medrobust 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. fillpattern and medrobust 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 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.
Top medrobust alternatives in Analytics are ranked by recent ship velocity. Browse the "medrobust alternatives" section above for the current picks, or visit /alternatives/medrobust for the full list with editorial commentary on each.