rjd3highfreq
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Comparison · Analytics
ggstatsplot vs modeltime.resample
A side-by-side editorial comparison of ggstatsplot and modeltime.resample — release velocity, themes, recent moves, and the top alternatives to consider.
ggstatsplot vs modeltime.resample: 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.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.
ggstatsplot vs modeltime.resample: 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.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 ggstatsplot 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 ggstatsplot or modeltime.resample.
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.resample alternatives →
Recent activity from ggstatsplot and modeltime.resample
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.resampletune 2.0 support, deterministic seeding, clearer errors
- 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
Frequently asked questions
What is the difference between ggstatsplot and modeltime.resample?
They serve adjacent needs but don't currently overlap on shipped themes. ggstatsplot 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 ggstatsplot better than modeltime.resample?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstatsplot 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 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.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.