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Comparison · Infra & APIs

FoRecoML vs sps

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

Shared themes:r-package

FoRecoML vs sps: at a glance

FeatureFoRecoMLsps
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themesforecasting, machine-learning, hierarchical-reconciliation, time-seriesr-package, survey-sampling, sequential-poisson, performance
Last editorial update52m ago1d 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 sps?

sps keeps sanding down sequential Poisson sampling rather than adding to it.

The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.

Read the full sps trajectory →

FoRecoML vs sps: 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.

S
sps
INFRA · APIS
2.5

sps keeps sanding down sequential Poisson sampling rather than adding to it.

◆ Current state

The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.

◆ Where it's heading

Development is consolidation rather than expansion. Most releases either speed up an existing routine or remove a decision the user previously had to make by hand, such as picking the smallest parameter that keeps replicate weights non-negative. Documentation and tooling get comparable attention to the algorithms, with a dedicated vignette on inclusion probabilities and a recent switch of test and documentation infrastructure. The API surface has been essentially stable across the window.

◆ Prediction

Expect continued small ergonomic and performance releases against the existing function set rather than new sampling designs, which is the pattern every release in this window follows.

Alternatives to FoRecoML and sps

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 sps.

See all FoRecoML alternatives → · See all sps alternatives →

Recent activity from FoRecoML and sps

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

  1. 1mo agospsDocumentation polish; switches to tinytest and litedown
  2. 1mo agoFoRecoMLStructured print and summary for fitted reconciliation models
  3. 1mo agoFoRecoMLAdopts FoReco's foreco class for all reconciliation output
  4. 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN
  5. 9mo agospsFixes extra argument handling in sps_iterator()
  6. 0y agospsAdds divisor_method() and a one-unit-at-a-time sampling iterator
  7. 1y agospsAdds an inclusion-probability vignette and faster partial sorting
  8. 1y agospsAutomatic tau selection for replicate weights
  9. 2y agospsAdds becomes_ta() for take-all stratum sample sizes

Frequently asked questions

What is the difference between FoRecoML and sps?

Both compete on the same themes — r-package — within Infra & APIs. sps 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 sps?

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

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