fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
A side-by-side editorial comparison of medrobust and randomwalk — release velocity, themes, recent moves, and the top alternatives to consider.
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.
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.
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.
A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.
The package is being built as a browser artifact first and an R package second: the readme, the vignettes and the release notes all point at a hosted dashboard rather than at library(). The last release completes that by making the compiled WebAssembly build installable by anyone via webr::install(), which turns the deployment work into something reusable outside this project. Version numbers are unreliable here — v0.2.0 was published two weeks after v1.0.2 — so read the dates, not the tags.
With the webR repository published, the next work most likely moves back to the simulation itself, though the entries give no direct evidence of planned features.
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 medrobust or randomwalk.
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.
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
See all medrobust alternatives → · See all randomwalk alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r package — within Analytics. medrobust and randomwalk 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. medrobust and randomwalk 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 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.
Top randomwalk alternatives in Analytics are ranked by recent ship velocity. Browse the "randomwalk alternatives" section above for the current picks, or visit /alternatives/randomwalk for the full list with editorial commentary on each.