randomwalk
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
Comparison · Analytics
forecasting vs ggstats
A side-by-side editorial comparison of forecasting and ggstats — release velocity, themes, recent moves, and the top alternatives to consider.
forecasting vs ggstats: at a glance
What is forecasting?
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
What is ggstats?
ggstats keeps widening what a coefficient or Likert plot can be
ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.
forecasting vs ggstats: editorial side-by-side
forecasting
0.0ANALYTICS
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
◆ Current state
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
◆ Where it's heading
The release pattern is maintenance on an eight-year cadence dictated entirely by the surrounding ecosystem: 1.1.1 rebuilt under R 4.0.4, 1.1.2 under R 4.3.2, 1.1.3 under R 4.6.1, each reporting whether the numbers moved. They mostly have not — the recurring note is minor numerical differences confined to the prophet forecasts in vignette('CHILI_prophet'). The only substantive change in the visible history is 1.1.0's methodological tidy-up of the scoring comparisons.
◆ Prediction
Nothing in these entries points to new functionality; the next release is most likely another vignette rebuild whenever a dependency change or a CRAN check failure forces one.
ggstats
0.0ANALYTICS
ggstats keeps widening what a coefficient or Likert plot can be
◆ Current state
ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.
◆ Where it's heading
Two long-running threads. The coefficient side has been consolidating — ggcoef_multinom() and ggcoef_multicomponents() soft-deprecated in favour of a unified ggcoef_model() with group_by, plus new ggcoef_dodged() and ggcoef_faceted() variants. The Likert side keeps expanding outward instead, absorbing survey objects, total columns and side-by-side layouts. Underneath both is a steady tax of ggplot2 and vctrs compatibility work, including tracking the geom_errorbarh() deprecation in ggplot2 4.0.0.
◆ Prediction
Expect gglikert_side() to lose its experimental status once its interface settles, and the deprecated multinomial entry points to be removed in a future release now that ggcoef_model() covers their cases.
Alternatives to forecasting and ggstats
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 forecasting or ggstats.
fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
abclass
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
See all forecasting alternatives → · See all ggstats alternatives →
Recent activity from forecasting and ggstats
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoforecastingVignettes rebuilt under R 4.6.1
- 5mo agoggstatsgglikert_side() and total columns for Likert plots
- 7mo agoggstatsLikert functions accept survey objects
- 11mo agoggstatsTable output for ggcoef_compare(); x-axis limits harmonised
- 1y agoggstatsggstats 0.10.0
- 1y agoggstatsCoefficient plots unified around ggcoef_model() with grouping
- 1y agoggstatsDiverging and Likert geoms redesigned; connector geoms added
- 2y agoforecastingVignettes rebuilt under R 4.3.2
- 5y agoforecastingVignettes rebuilt under R 4.0.4
- 7y agoforecastingStandard PIT and discretized log-normal scoring
- 7y agoforecastingThe version used for the book chapter, with pinned dependencies
Frequently asked questions
What is the difference between forecasting and ggstats?
They serve adjacent needs but don't currently overlap on shipped themes. forecasting and ggstats 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 forecasting better than ggstats?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. forecasting and ggstats 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 forecasting?
Top forecasting alternatives in Analytics are ranked by recent ship velocity. Browse the "forecasting alternatives" section above for the current picks, or visit /alternatives/forecasting for the full list with editorial commentary on each.
What are the best alternatives to ggstats?
Top ggstats alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstats alternatives" section above for the current picks, or visit /alternatives/ggstats for the full list with editorial commentary on each.