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Comparison · Infra & APIs

FoRecoML vs rgm

A side-by-side editorial comparison of FoRecoML and rgm — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

FoRecoML vs rgm: at a glance

FeatureFoRecoMLrgm
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, machine-learning, hierarchical-reconciliation, time-seriesmicrobiome, graphical-models, bayesian-inference, cran-maintenance
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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.

Read the full FoRecoML trajectory →

What is rgm?

A microbiome network model that got itself un-archived by deleting the dependency that killed it.

rgm implements the random graphical model for microbiome interactions across related environments, published in JABES in 2026. The package was archived from CRAN in February 2026 because of its dependency on huge; the recovery release drops that dependency entirely, which cost it the graphical-lasso warm start that used to seed the initial graph — the default is now an empty graph, with warm starts left to the user. A post-processing function returning ggplot diagnostics arrived in the same release.

Read the full rgm trajectory →

FoRecoML vs rgm: editorial side-by-side

F
FoRecoML
INFRA · APIS
0.0

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.

R
rgm
INFRA · APIS
0.0

A microbiome network model that got itself un-archived by deleting the dependency that killed it.

◆ Current state

rgm implements the random graphical model for microbiome interactions across related environments, published in JABES in 2026. The package was archived from CRAN in February 2026 because of its dependency on huge; the recovery release drops that dependency entirely, which cost it the graphical-lasso warm start that used to seed the initial graph — the default is now an empty graph, with warm starts left to the user. A post-processing function returning ggplot diagnostics arrived in the same release.

◆ Where it's heading

Three tags shipped inside two hours on one day, and the notes are candid about why: 1.1.0 held the actual work but was never released, 1.2.0 restated it under a higher version to signal the size of the change, and 1.2.1 answered CRAN pre-test feedback. Beyond the archival recovery, the visible work is housekeeping that had accumulated — a shadowed rmvnorm() definition, roxygen import tags that were silently emitting nothing, leftover C++ template scaffolding, and build artifacts under version control. The diagnostics function is the only genuinely new user-facing capability in the window.

◆ Prediction

The immediate task was restoring availability, and that is done; the open question the entries raise is whether losing the graphical-lasso warm start affects convergence in practice, which the new diagnostic plots are positioned to answer.

Alternatives to FoRecoML and rgm

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 rgm.

See all FoRecoML alternatives → · See all rgm alternatives →

Recent activity from FoRecoML and rgm

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoFoRecoMLStructured print and summary for fitted reconciliation models
  2. 1mo agoFoRecoMLAdopts FoReco's foreco class for all reconciliation output
  3. 3mo agorgmJournal DOI replaces the preprint; promotional wording removed
  4. 3mo agorgmBack on CRAN after dropping the dependency that caused archival
  5. 3mo agorgmUnreleased twin of the CRAN recovery release
  6. 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN
  7. 2y agorgmFirst release: simulation, estimation and post-processing

Frequently asked questions

What is the difference between FoRecoML and rgm?

Both compete on the same themes — r-package — within Infra & APIs. FoRecoML and rgm 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.

Is FoRecoML better than rgm?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. FoRecoML and rgm 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 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 rgm?

Top rgm alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "rgm alternatives" section above for the current picks, or visit /alternatives/rgm for the full list with editorial commentary on each.