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 robma and singlercapture — release velocity, themes, recent moves, and the top alternatives to consider.
RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy
RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.
singleRcapture reached 1.0.0 with no release notes at all — the arc has to be read backwards.
A package for single-source capture-recapture population size estimation: zero-truncated Poisson, geometric and negative binomial regression, Chao and Zelterman mixture models, analytic and bootstrap variance estimation, all behind estimatePopsize(). The 0.2.x line professionalised it — an offset argument, parallel bootstrap and dfbeta, faster semiparametric sampling, a singleRStaticCountData subclass explicitly created so a companion package could fit models from countreg and VGAM, then interaction-term and anova fixes. The 1.0.0 release carries nothing but a link to the compare view.
RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.
The 3.x series solved the modeling problem and left an interface problem behind: a caller had to know which of six constructors matched their data type, and argument names differed across them. 4.0.0 resolves that by making the model family a set of arguments rather than a function name, and by standardizing input naming on metafor-style conventions. It shipped one day after BayesTools 0.3.0, the author's own upstream infrastructure package, whose new standardization and prior-transformation machinery this rewrite depends on.
A rewrite this wide usually needs a follow-up, so expect 4.0.x patches addressing migration gaps as users hit the removed constructors and renamed arguments.
A package for single-source capture-recapture population size estimation: zero-truncated Poisson, geometric and negative binomial regression, Chao and Zelterman mixture models, analytic and bootstrap variance estimation, all behind estimatePopsize(). The 0.2.x line professionalised it — an offset argument, parallel bootstrap and dfbeta, faster semiparametric sampling, a singleRStaticCountData subclass explicitly created so a companion package could fit models from countreg and VGAM, then interaction-term and anova fixes. The 1.0.0 release carries nothing but a link to the compare view.
The direction visible in 0.2.x is outward: refactoring for maintainability, extending to models fitted elsewhere via a subclass, adding a JSS-paper vignette, and pushing coverage towards 90%. That is a package preparing to be cited and extended rather than one still finding its methods. The 1.0.0 tag presumably marks the end of that stabilisation, but the entry itself gives no evidence either way.
Not readable from this feed — the 1.0.0 notes are empty, so whether the major version marks an API freeze or a breaking change cannot be determined from the entries shown.
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 robma or singlercapture.
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 robma alternatives → · See all singlercapture alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. robma and singlercapture 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. robma and singlercapture 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 robma alternatives in Analytics are ranked by recent ship velocity. Browse the "robma alternatives" section above for the current picks, or visit /alternatives/robma for the full list with editorial commentary on each.
Top singlercapture alternatives in Analytics are ranked by recent ship velocity. Browse the "singlercapture alternatives" section above for the current picks, or visit /alternatives/singlercapture for the full list with editorial commentary on each.