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Comparison · Infra & APIs
FoRecoML vs missSBM
A side-by-side editorial comparison of FoRecoML and missSBM — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
FoRecoML vs missSBM: 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 missSBM?
missSBM returns after four dormant years with a stricter API and a new refinement step.
The package fits stochastic block models to networks with missing data, covering both missing-at-random and informative sampling designs. After a run of releases from 2019 to 2022, the feed goes quiet until this year's 1.1.0, which breaks the control interface, exposes the block split and merge operations as testable instance methods, and adds a node-swap refinement pass that runs after variational convergence.
FoRecoML vs missSBM: 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.
missSBM
2.5INFRA · APIS
missSBM returns after four dormant years with a stricter API and a new refinement step.
◆ Current state
The package fits stochastic block models to networks with missing data, covering both missing-at-random and informative sampling designs. After a run of releases from 2019 to 2022, the feed goes quiet until this year's 1.1.0, which breaks the control interface, exposes the block split and merge operations as testable instance methods, and adds a node-swap refinement pass that runs after variational convergence.
◆ Where it's heading
The new release is maintenance-driven in the best sense: it targets the parts of the codebase that were hard to test or easy to misuse. Replacing free-form control lists with a function of named, defaulted arguments turns silent typos into errors, and pulling the exploration logic out of the collection class makes the search algorithm independently testable without changing it. The polish step addresses a known weakness, reaching individually misclassified nodes that split and merge moves cannot fix.
◆ Prediction
Given the gap before this release, the near-term question is whether the cadence resumes at all; the refactoring it contains would support further algorithmic work if it does.
Alternatives to FoRecoML and missSBM
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 missSBM.
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 missSBM alternatives →
Recent activity from FoRecoML and missSBM
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 27d agomissSBMReplaces raw control lists with missSBM_param(), adds polish()
- 1mo agoFoRecoMLStructured print and summary for fitted reconciliation models
- 1mo agoFoRecoMLAdopts FoReco's foreco class for all reconciliation output
- 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN ⚡
- 3y agomissSBMAdapts to Matrix 1.4-2 and fixes HTML5 documentation
- 4y agomissSBMFixes linking against nloptR 2.0.0
- 5y agomissSBMRelaxes CRAN test tolerances to avoid random failures
- 5y agomissSBMRewrites optimisation in C++ armadillo with sparse matrices
- 5y agomissSBMRenames core functions and interfaces with the sbm package
Frequently asked questions
What is the difference between FoRecoML and missSBM?
Both compete on the same themes — r-package — within Infra & APIs. missSBM 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 missSBM?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. missSBM 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 missSBM?
Top missSBM alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "missSBM alternatives" section above for the current picks, or visit /alternatives/misssbm for the full list with editorial commentary on each.