RMVMR
RMVMR is being tidied in lockstep with MVMR, the package it wraps
Comparison · Analytics
modeltime.ensemble vs modeltime.resample
A side-by-side editorial comparison of modeltime.ensemble and modeltime.resample — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodelscompatibility maintenancer package
modeltime.ensemble vs modeltime.resample: at a glance
| Feature | modeltime.ensemble | modeltime.resample |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | time series forecasting, ensembles, tidymodels, compatibility maintenance | time series, cross-validation, tidymodels, compatibility maintenance |
| Last editorial update | 1h ago | 1h ago |
| Website | Visit → | 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.
What is modeltime.resample?
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
modeltime.ensemble vs modeltime.resample: editorial side-by-side
modeltime.ensemble
0.0ANALYTICS
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.
modeltime.resample
0.0ANALYTICS
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
◆ Current state
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
◆ Where it's heading
Every entry here is compatibility work against something upstream — hardhat 1.0.0, workflows regression mode, then tune 2.0.0 twice. The 0.3.0 notes show a second concern emerging alongside it: making failures legible, with .notes on failed fits, actionable errors from unnest_modeltime_resamples(), and fallback logic when prediction columns go missing across versions. Reproducibility gets the same treatment through explicit seeding.
◆ Prediction
Expect the next release to track the next tidymodels breaking change, with any new work continuing on error reporting rather than resampling strategies.
Alternatives to modeltime.ensemble and modeltime.resample
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 modeltime.resample.
geoarrow-r
geoarrow tracks the GeoArrow spec and otherwise just keeps compiling
n2khab
n2khab keeps retracting interpretations of habitat data it can't actually support
tidypolars
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
OneSampleMR
OneSampleMR found that argument order in a formula was silently changing its estimates
bpbounds
bpbounds found the same swapped-cell bug twice and clamped its bounds back into range
See all modeltime.ensemble alternatives → · See all modeltime.resample alternatives →
Recent activity from modeltime.ensemble and modeltime.resample
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agomodeltime.ensembleRealigned for tune 2.0.0 resampling changes
- 11mo agomodeltime.resampletune 2.0 support, deterministic seeding, clearer errors
- 11mo agomodeltime.ensembleDrops the tidyverse dependency ahead of tune 2.0
- 11mo agomodeltime.resampleDependency cleanup ahead of the next tune release
- 3y agomodeltime.resampleFixes workflows in regression mode
- 4y agomodeltime.resampleUpdates for hardhat 1.0.0
- 5y agomodeltime.ensemblePer-series calibration IDs and parallel refitting
- 5y agomodeltime.ensembleRecursive ensembles for single and panel series ⚡
Frequently asked questions
What is the difference between modeltime.ensemble and modeltime.resample?
Both compete on the same themes — tidymodels, compatibility maintenance, r package — within Analytics. modeltime.ensemble and modeltime.resample 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 modeltime.resample?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modeltime.ensemble and modeltime.resample 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 modeltime.resample?
Top modeltime.resample alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime.resample alternatives" section above for the current picks, or visit /alternatives/modeltime-resample for the full list with editorial commentary on each.