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Comparison · Infra & APIs
FoRecoML vs nuggets
A side-by-side editorial comparison of FoRecoML and nuggets — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
FoRecoML vs nuggets: at a glance
What is FoRecoML?
The machine-learning arm of a forecast reconciliation toolkit, four months old and already sharing its sibling's plumbing.
FoRecoML brings machine-learning approaches to forecast reconciliation across cross-sectional, temporal, and cross-temporal frameworks through csrml(), terml(), and ctrml(). It reached CRAN in April 2026 and has since spent both releases integrating with FoReco rather than expanding its own method set: results are now FoReco's foreco objects, and print() and summary() report framework, approach, problem dimensions, features, training sample size, combination matrix, and trained models.
What is nuggets?
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.
FoRecoML vs nuggets: editorial side-by-side
FoRecoML
0.0INFRA · APIS
The machine-learning arm of a forecast reconciliation toolkit, four months old and already sharing its sibling's plumbing.
◆ Current state
FoRecoML brings machine-learning approaches to forecast reconciliation across cross-sectional, temporal, and cross-temporal frameworks through csrml(), terml(), and ctrml(). It reached CRAN in April 2026 and has since spent both releases integrating with FoReco rather than expanding its own method set: results are now FoReco's foreco objects, and print() and summary() report framework, approach, problem dimensions, features, training sample size, combination matrix, and trained models.
◆ Where it's heading
This package is being built as a satellite, not a competitor. Adopting FoReco's exported new_foreco_class() constructor within days of that class appearing means FoRecoML results drop straight into the same print, summary, plot, and components methods as analytically reconciled ones — which is what makes machine-learning and classical reconciliation directly comparable in a single workflow. The 1.1.1 argument-validation work landed in the same minute as the equivalent change in FoReco, so the two are being maintained as one release train.
◆ Prediction
With the integration work done, the next release is more likely to add or expose machine-learning approaches than to keep reshaping output; the structured summary already enumerates features and trained models, which suggests inspection tooling is where attention has been.
nuggets
2.5INFRA · APIS
nuggets keeps compounding on the 2.0 rewrite — more pattern families, lighter install.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to FoRecoML and nuggets
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 FoRecoML or nuggets.
forestploter
A forest plot package that keeps handing users control of one more graphical detail.
ggInterval
Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.
rgm
A microbiome network model that got itself un-archived by deleting the dependency that killed it.
contagionchannels
Three releases in ten days, every one of them a CRAN reviewer's correction rather than a code change.
tidyaudit
Pipeline provenance for tidyverse workflows, recording what changed at each step without keeping the data.
See all FoRecoML alternatives → · See all nuggets alternatives →
Recent activity from FoRecoML and nuggets
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 27d agonuggetsSparse bit chain speeds dig(); explore() gains clustering
- 1mo agoFoRecoMLStructured print and summary for fitted reconciliation models
- 1mo agoFoRecoMLAdopts FoReco's foreco class for all reconciliation output
- 2mo agonuggetspartition() gains .subsets; geom_diamond() layout improved
- 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN ⚡
- 5mo agonuggetsexplore() covers contrasts and correlations; dig_ancestors() added
- 6mo agonuggetsCritical explore() bug fixed; is_logicalish() added
- 6mo agonuggetsShiny deps moved to Suggests; BH and RcppThread dropped
- 8mo agonuggetscluster_associations() and add_interest() arrive; C++ condition parser
Frequently asked questions
What is the difference between FoRecoML and nuggets?
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.
Is FoRecoML better than nuggets?
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.
What are the best alternatives to FoRecoML?
Top FoRecoML alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "FoRecoML alternatives" section above for the current picks, or visit /alternatives/forecoml for the full list with editorial commentary on each.
What are the best alternatives to nuggets?
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.