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Comparison · Infra & APIs

FoRecoML vs projoint

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

Shared themes:r-package

FoRecoML vs projoint: at a glance

FeatureFoRecoMLprojoint
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themesforecasting, machine-learning, hierarchical-reconciliation, time-seriesconjoint-analysis, survey-research, qualtrics, cran
Last editorial update54m 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 projoint?

projoint spent a year on CRAN paperwork, then shipped a correctness fix it flagged itself.

projoint is an R package for analysing conjoint survey experiments, covering Qualtrics import, reshaping, and quantity-of-interest estimation with inter-rater reliability correction. Most of its release history is CRAN admission work — citation formats, DESCRIPTION fields, \value{} tags, vignette cleanups — with four tags backfilled within ninety seconds of each other on 15 July in non-monotonic version order, so neither tag order nor timestamps in this feed track the real sequence. The substantive releases are the ones fixing data-preparation bugs that silently corrupt estimates.

Read the full projoint trajectory →

FoRecoML vs projoint: 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.

P
projoint
INFRA · APIS
2.5

projoint spent a year on CRAN paperwork, then shipped a correctness fix it flagged itself.

◆ Current state

projoint is an R package for analysing conjoint survey experiments, covering Qualtrics import, reshaping, and quantity-of-interest estimation with inter-rater reliability correction. Most of its release history is CRAN admission work — citation formats, DESCRIPTION fields, \value{} tags, vignette cleanups — with four tags backfilled within ninety seconds of each other on 15 July in non-monotonic version order, so neither tag order nor timestamps in this feed track the real sequence. The substantive releases are the ones fixing data-preparation bugs that silently corrupt estimates.

◆ Where it's heading

The maintainer is hardening the path from raw Qualtrics export to estimate, which is where conjoint analysis quietly goes wrong. Three separate releases fix that path: dropped respondent-level weights in organize_data(), repeated-task reshaping in reshape_projoint(), and choice-to-profile mapping in 1.1.3. Each fix now arrives with regression tests and stricter validation rather than just a patch, and 1.1.3 adds an explicit .choice_map so the mapping is auditable instead of inferred.

◆ Prediction

Expect the validation-and-regression-test pattern to keep extending across the import path, with releases continuing to arrive in bursts around CRAN submission rather than on a cadence.

Alternatives to FoRecoML and projoint

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 projoint.

See all FoRecoML alternatives → · See all projoint alternatives →

Recent activity from FoRecoML and projoint

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

  1. 17d agoprojointExplicit .choice_map guards choice-to-profile mapping
  2. 1mo agoprojointCRAN submission housekeeping for DESCRIPTION and examples
  3. 1mo agoprojointCRAN formatting pass; minor make_projoint_data() fix
  4. 1mo agoprojointreshape_projoint() repeated-task bug fixed; validation tightened
  5. 1mo agoprojointCitation metadata updated with the CRAN DOI
  6. 1mo agoFoRecoMLStructured print and summary for fitted reconciliation models
  7. 1mo agoFoRecoMLAdopts FoReco's foreco class for all reconciliation output
  8. 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN
  9. 5mo agoprojointorganize_data() no longer drops respondent-level weights

Frequently asked questions

What is the difference between FoRecoML and projoint?

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

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

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