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errors vs modeltime.ensemble

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

errors vs modeltime.ensemble: at a glance

Featureerrorsmodeltime.ensemble
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesuncertainty-propagation, measurement, r-quantities, formattingtime series forecasting, ensembles, tidymodels, compatibility maintenance
Last editorial update1h ago9h ago
WebsiteVisit →Visit →

What is errors?

errors keeps making uncertainty print the way each scientific field expects.

errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.

Read the full errors trajectory →

What is modeltime.ensemble?

modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.

modeltime.ensemble builds average, weighted and stacked ensembles over modeltime forecast models. After a four-year gap it shipped twice in a fortnight during August and September 2025, both releases devoted to tracking breaking changes in tidymodels' tune package — new resampling column conventions, key uniqueness across resamples, recipe preparation. The tidyverse dependency was dropped in the same pass.

Read the full modeltime.ensemble trajectory →

errors vs modeltime.ensemble: editorial side-by-side

E
errors
ANALYTICS
0.0

errors keeps making uncertainty print the way each scientific field expects.

◆ Current state

errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.

◆ Where it's heading

Two threads run through this history. One is formatting convergence: uncertainty has field-specific conventions, and the package has been absorbing them one contributed pull request at a time rather than imposing a single style. The other is keeping the errors class first-class everywhere R users work — vctrs methods for dplyr 1.0, a geom_errors() layer for ggplot2, missing-value and duplicate handling. Both are integration work, which is what a type-extension package mostly is.

◆ Prediction

Expect further formatting conventions to arrive as contributions, following PDG rounding and the decimals option, plus continued upkeep against ggplot2 aesthetic deprecations that have forced two of the last four releases.

M0.0

modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.

◆ Current state

modeltime.ensemble builds average, weighted and stacked ensembles over modeltime forecast models. After a four-year gap it shipped twice in a fortnight during August and September 2025, both releases devoted to tracking breaking changes in tidymodels' tune package — new resampling column conventions, key uniqueness across resamples, recipe preparation. The tidyverse dependency was dropped in the same pass.

◆ Where it's heading

This is a package whose forecasting capability was settled by 2021 — recursive ensembles, per-series calibration — and whose recent life is dictated entirely by upstream tidymodels churn. New contributors did that compatibility work, including one from the tidymodels side. It now requires tune 2.0.0 and modeltime.resample 0.3.0, pinning it to the current tidymodels generation rather than straddling versions.

◆ Prediction

Expect the next release to follow the next tune or modeltime.resample breaking change rather than to introduce new ensembling methods.

Alternatives to errors and modeltime.ensemble

Other Analytics 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 errors or modeltime.ensemble.

See all errors alternatives → · See all modeltime.ensemble alternatives →

Recent activity from errors and modeltime.ensemble

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

  1. 11mo agomodeltime.ensembleRealigned for tune 2.0.0 resampling changes
  2. 11mo agomodeltime.ensembleDrops the tidyverse dependency ahead of tune 2.0
  3. 1y agoerrorserrors 0.4.4 replaces deprecated geom_errorbarh()
  4. 1y agoerrorserrors 0.4.3 supports decimals in parenthesis notation
  5. 2y agoerrorserrors 0.4.2 adds PDG rounding rules
  6. 2y agoerrorserrors 0.4.1 handles missing values, fixes na.rm
  7. 3y agoerrorserrors 0.4.0 adds geom_errors() for automatic errorbars
  8. 5y agomodeltime.ensemblePer-series calibration IDs and parallel refitting
  9. 5y agomodeltime.ensembleRecursive ensembles for single and panel series
  10. 5y agoerrorserrors 0.3.6

Frequently asked questions

What is the difference between errors and modeltime.ensemble?

They serve adjacent needs but don't currently overlap on shipped themes. errors and modeltime.ensemble 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 errors better than modeltime.ensemble?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. errors and modeltime.ensemble 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 Analytics products to evaluate alongside.

What are the best alternatives to errors?

Top errors alternatives in Analytics are ranked by recent ship velocity. Browse the "errors alternatives" section above for the current picks, or visit /alternatives/errors-r for the full list with editorial commentary on each.

What are the best alternatives to modeltime.ensemble?

Top modeltime.ensemble alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime.ensemble alternatives" section above for the current picks, or visit /alternatives/modeltime-ensemble for the full list with editorial commentary on each.