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Comparison · Analytics

modeltime.ensemble vs OneSampleMR

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

modeltime.ensemble vs OneSampleMR: at a glance

Featuremodeltime.ensembleOneSampleMR
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestime series forecasting, ensembles, tidymodels, compatibility maintenancemendelian randomization, r, instrumental variables, epidemiology
Last editorial update2h ago1h 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 OneSampleMR?

OneSampleMR found that argument order in a formula was silently changing its estimates

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

Read the full OneSampleMR trajectory →

modeltime.ensemble vs OneSampleMR: 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.

O
OneSampleMR
ANALYTICS
0.0

OneSampleMR found that argument order in a formula was silently changing its estimates

◆ Current state

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

◆ Where it's heading

Two threads. The first is reach — fsw() now reads models fitted by AER::ivreg(), estimatr::iv_robust() and fixest::feols() in addition to ivreg::ivreg(), which makes conditional F statistics available without refitting in the package's own idiom. The second is hardening: clear errors when more than one exposure is given or when a variable collides with the reserved name y, and print methods that no longer fail on user-specified t0 with log or logit links. Both come largely from user reports rather than a plan.

◆ Prediction

The estimator-support work has been adding one IV-fitting package at a time on outside contributions, so further backends are the likeliest next content — the package's own estimators have been stable since first release.

Alternatives to modeltime.ensemble and OneSampleMR

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 OneSampleMR.

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

Recent activity from modeltime.ensemble and OneSampleMR

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

  1. 1mo agoOneSampleMROneSampleMR fixes estimates broken by covariate order in the formula
  2. 5mo agoOneSampleMROneSampleMR computes conditional F for three more IV packages
  3. 11mo agomodeltime.ensembleRealigned for tune 2.0.0 resampling changes
  4. 11mo agomodeltime.ensembleDrops the tidyverse dependency ahead of tune 2.0
  5. 1y agoOneSampleMROneSampleMR 0.1.6
  6. 2y agoOneSampleMROneSampleMR 0.1.5
  7. 2y agoOneSampleMROneSampleMR 0.1.4
  8. 3y agoOneSampleMROneSampleMR 0.1.3
  9. 5y agomodeltime.ensemblePer-series calibration IDs and parallel refitting
  10. 5y agomodeltime.ensembleRecursive ensembles for single and panel series

Frequently asked questions

What is the difference between modeltime.ensemble and OneSampleMR?

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

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

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