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Comparison · Analytics
ggstatsplot vs modeltime.ensemble
A side-by-side editorial comparison of ggstatsplot and modeltime.ensemble — release velocity, themes, recent moves, and the top alternatives to consider.
ggstatsplot vs modeltime.ensemble: at a glance
What is ggstatsplot?
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
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.
ggstatsplot vs modeltime.ensemble: editorial side-by-side
ggstatsplot
0.0ANALYTICS
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
◆ Current state
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
◆ Where it's heading
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
◆ Prediction
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
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.
Alternatives to ggstatsplot 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 ggstatsplot or modeltime.ensemble.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all ggstatsplot alternatives → · See all modeltime.ensemble alternatives →
Recent activity from ggstatsplot and modeltime.ensemble
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
- 4mo agoggstatsplotInternal maintenance only
- 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
- 8mo agoggstatsplotContributor list updated in DESCRIPTION
- 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
- 11mo agoggstatsplotAdapted to the latest ggplot2 release
- 11mo agomodeltime.ensembleRealigned for tune 2.0.0 resampling changes
- 11mo agomodeltime.ensembleDrops the tidyverse dependency ahead of tune 2.0
- 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 ggstatsplot and modeltime.ensemble?
They serve adjacent needs but don't currently overlap on shipped themes. ggstatsplot 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 ggstatsplot better than modeltime.ensemble?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstatsplot 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 ggstatsplot?
Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot 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.