exametrika
A test-theory package that grew into a graphical-model toolkit, now spending its releases paying down the API debt that growth created.
A side-by-side editorial comparison of cocoon and nuggets — release velocity, themes, recent moves, and the top alternatives to consider.
A statistics-formatting helper in maintenance mode, tracking R-devel one fix at a time
cocoon formats statistical output for manuscripts, converting model and test objects into publication-ready strings. Its surface settled early: format_stats() is a generic that dispatches on object class, introduced in 0.1.0 to supersede the earlier format_corr() and format_ttest(), and extended in 0.2.0 to cover aov, lm, glm and the lme4 and lmerTest mixed-model families. The two releases since have been single-issue compatibility fixes against changes to wilcox.test() in R-devel.
nuggets keeps compounding on the 2.0 rewrite — more pattern families, lighter install.
nuggets searches for association rules, contrasts and other conditional patterns in the GUHA tradition, with a C++ core behind dig() and an interactive explore() app for reading results. Since the 2.0 rewrite of that core, every release has widened the same three surfaces: more pattern families to mine, more of explore() to inspect them in, and steady performance work underneath. The most recent tag optimises dig() on sparse crisp data with a sparse bit chain and adds clustering characteristics to explore() for association rules.
cocoon formats statistical output for manuscripts, converting model and test objects into publication-ready strings. Its surface settled early: format_stats() is a generic that dispatches on object class, introduced in 0.1.0 to supersede the earlier format_corr() and format_ttest(), and extended in 0.2.0 to cover aov, lm, glm and the lme4 and lmerTest mixed-model families. The two releases since have been single-issue compatibility fixes against changes to wilcox.test() in R-devel.
The package reached feature completeness for its stated job quickly and has been in maintenance since early 2025. Both 0.2.1 and 0.3.1 address the same upstream moving part - how wilcox.test() computes exact versus asymptotic distributions in development versions of R - which is the shape of a package whose own code is stable and whose risk lives entirely in what it wraps. Nothing in the recent entries points at new statistical object types.
Further releases are likely to stay reactive, triggered by R-devel or dependency changes rather than by new formatting methods, unless a specific model class is requested.
nuggets searches for association rules, contrasts and other conditional patterns in the GUHA tradition, with a C++ core behind dig() and an interactive explore() app for reading results. Since the 2.0 rewrite of that core, every release has widened the same three surfaces: more pattern families to mine, more of explore() to inspect them in, and steady performance work underneath. The most recent tag optimises dig() on sparse crisp data with a sparse bit chain and adds clustering characteristics to explore() for association rules.
Two forces are shaping the package. One is coverage: baseline, complement and paired-baseline contrasts, correlations, tautologies, ancestors and clustering have all been added as first-class dig_ or explore_ surfaces, so the same search engine now answers a widening set of questions. The other is weight — Shiny packages moved from Imports to Suggests, BH and RcppThread dropped, XSIMD updated, parse_condition() rewritten in C++ — which keeps a package with an interactive app from forcing that app's dependencies on every user. Deprecations are handled through lifecycle rather than removed abruptly.
Expect the sparse-data optimisation to extend from crisp to fuzzy data, and explore() to keep gaining tabs as each new pattern family lands, on the roughly six-week cadence the 2.2 line has held.
Other Infra & APIs 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 cocoon or nuggets.
A test-theory package that grew into a graphical-model toolkit, now spending its releases paying down the API debt that growth created.
projoint spent a year on CRAN paperwork, then shipped a correctness fix it flagged itself.
eratosthenes spends 0.1.0 hardening inputs rather than adding chronology methods.
dqcheckr adds drift analysis, then removes the YAML a user had to hand-write.
An actuarial mainstay spends its releases on CI plumbing, not on new mathematics.
EDAForge is a data-quality auditor renamed mid-flight, still finding its CRAN footing.
See all cocoon alternatives → · See all nuggets alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. nuggets is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. nuggets is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top cocoon alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "cocoon alternatives" section above for the current picks, or visit /alternatives/cocoon for the full list with editorial commentary on each.
Top nuggets alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "nuggets alternatives" section above for the current picks, or visit /alternatives/nuggets for the full list with editorial commentary on each.