← Back to home
Comparison · Infra & APIs

FoRecoML vs tidyaudit

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

Shared themes:r-package

FoRecoML vs tidyaudit: at a glance

FeatureFoRecoMLtidyaudit
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, machine-learning, hierarchical-reconciliation, time-seriesdata-quality, provenance, tidyverse, pipeline-auditing
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 tidyaudit?

Pipeline provenance for tidyverse workflows, recording what changed at each step without keeping the data.

tidyaudit records lightweight metadata snapshots as data flows through a pipeline — row and column counts, NA counts, and structured diffs between any two points — without storing the data itself. Taps are operation-aware, so join, filter, and anti-join steps each report what that operation specifically did, and validation helpers cover join integrity, primary keys, and variable relationships. The trail can now be exported as a self-contained interactive HTML diagram or serialized to JSON or RDS.

Read the full tidyaudit trajectory →

FoRecoML vs tidyaudit: 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.

T
tidyaudit
INFRA · APIS
0.0

Pipeline provenance for tidyverse workflows, recording what changed at each step without keeping the data.

◆ Current state

tidyaudit records lightweight metadata snapshots as data flows through a pipeline — row and column counts, NA counts, and structured diffs between any two points — without storing the data itself. Taps are operation-aware, so join, filter, and anti-join steps each report what that operation specifically did, and validation helpers cover join integrity, primary keys, and variable relationships. The trail can now be exported as a self-contained interactive HTML diagram or serialized to JSON or RDS.

◆ Where it's heading

The arc is from inspection to artifact. The first release made the trail something you print and read; 0.2.0 made it something you can hand to someone else or feed to another program, with the HTML export deliberately requiring no server and no Shiny. Reporting has been refined in the same direction, with a tabular changes block showing from-and-to values with row, column, and NA deltas. The remaining work in the window is defensive — a factor-handling path rebuilt because R-devel tightened what as.data.frame.table() accepts in row names.

◆ Prediction

With serialization and a standalone export in place, the natural next step is making trails comparable across runs rather than only across steps within one, though nothing in the entries commits to it yet.

Alternatives to FoRecoML and tidyaudit

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 tidyaudit.

See all FoRecoML alternatives → · See all tidyaudit alternatives →

Recent activity from FoRecoML and tidyaudit

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 agotidyauditFactor auditing fixed against a stricter R-devel
  4. 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN
  5. 4mo agotidyauditTrails export to standalone HTML and machine-readable formats
  6. 5mo agotidyauditFirst release: pipeline audit trails for tidyverse

Frequently asked questions

What is the difference between FoRecoML and tidyaudit?

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

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

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