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Comparison · Analytics

modeltime.ensemble vs rjdqa

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

modeltime.ensemble vs rjdqa: at a glance

Featuremodeltime.ensemblerjdqa
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestime series forecasting, ensembles, tidymodels, compatibility maintenanceofficial-statistics, seasonal-adjustment, quality-assurance, r-package
Last editorial update7h ago54m ago
WebsiteVisit →Visit →

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 →

What is rjdqa?

rjdqa keeps refining one screen: the seasonal adjustment quality dashboard

rjdqa builds quality assessment dashboards for seasonal adjustment models produced by JDemetra+, aimed at official statisticians reviewing adjusted series. Essentially all development goes into two functions, simple_dashboard() and its denser variant simple_dashboard2(). Version 0.1.6 adds parameters to append observations to the forecast and to control whether the residual trading-days test is printed, defaulting to monthly series only, plus outlier table layout work and user-defined calendar regressor support in sc_dashboard().

Read the full rjdqa trajectory →

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

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.

R
rjdqa
ANALYTICS
0.0

rjdqa keeps refining one screen: the seasonal adjustment quality dashboard

◆ Current state

rjdqa builds quality assessment dashboards for seasonal adjustment models produced by JDemetra+, aimed at official statisticians reviewing adjusted series. Essentially all development goes into two functions, simple_dashboard() and its denser variant simple_dashboard2(). Version 0.1.6 adds parameters to append observations to the forecast and to control whether the residual trading-days test is printed, defaulting to monthly series only, plus outlier table layout work and user-defined calendar regressor support in sc_dashboard().

◆ Where it's heading

The package has converged on a single deliverable and is tuning it against reviewer practice. Each release adds a parameter that lets the analyst include or exclude one element of the dashboard, or adjusts how densely information is packed into the fixed space of the layout. The td_effect default — print the test only for monthly series — is characteristic: the knowledge about when a diagnostic is meaningful is being encoded into the tool rather than left to the reader.

◆ Prediction

The pattern of adding one toggle per diagnostic per release points at the same thing again, most likely another test given a conditional default, rather than a new dashboard function alongside the two that exist.

Alternatives to modeltime.ensemble and rjdqa

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 modeltime.ensemble or rjdqa.

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

Recent activity from modeltime.ensemble and rjdqa

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

  1. 9mo agorjdqaForecast observations and conditional trading-days test in dashboards
  2. 11mo agomodeltime.ensembleRealigned for tune 2.0.0 resampling changes
  3. 11mo agomodeltime.ensembleDrops the tidyverse dependency ahead of tune 2.0
  4. 1y agorjdqaFix tail() usage on ts objects
  5. 2y agorjdqaFix dependency minimums and outlier ordering
  6. 2y agorjdqasimple_dashboard2() added; deprecated sa_dashboard() removed
  7. 2y agorjdqasimple_dashboard() introduced; sa_dashboard() deprecated
  8. 5y agomodeltime.ensemblePer-series calibration IDs and parallel refitting
  9. 5y agomodeltime.ensembleRecursive ensembles for single and panel series
  10. 7y agorjdqaFirst CRAN release

Frequently asked questions

What is the difference between modeltime.ensemble and rjdqa?

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

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modeltime.ensemble and rjdqa 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 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.

What are the best alternatives to rjdqa?

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