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ggstatsplot vs rjd3highfreq

A side-by-side editorial comparison of ggstatsplot and rjd3highfreq — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

ggstatsplot vs rjd3highfreq: at a glance

Featureggstatsplotrjd3highfreq
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstatistical-plots, ggplot2, contingency-tables, hypothesis-testingseasonal-adjustment, time-series, jdemetra, r-package
Last editorial update1h ago47m ago
WebsiteVisit →Visit →

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.

Read the full ggstatsplot trajectory →

What is rjd3highfreq?

rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.

An R wrapper around JDemetra+ routines for seasonal adjustment of high-frequency time series, built on fractional airline decomposition. Only three releases are on record, roughly one every six months, and two of them describe nothing beyond updated .jar files. The package is a thin binding whose substance lives in the Java libraries it packages, and the release notes reflect that literally.

Read the full rjd3highfreq trajectory →

ggstatsplot vs rjd3highfreq: editorial side-by-side

G
ggstatsplot
ANALYTICS
0.0

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.

R
rjd3highfreq
ANALYTICS
0.0

rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.

◆ Current state

An R wrapper around JDemetra+ routines for seasonal adjustment of high-frequency time series, built on fractional airline decomposition. Only three releases are on record, roughly one every six months, and two of them describe nothing beyond updated .jar files. The package is a thin binding whose substance lives in the Java libraries it packages, and the release notes reflect that literally.

◆ Where it's heading

The one release with detail points at where the work actually is: 2.4.1 exposes eps and deps parameters on fractionalAirlineDecomposition(), controlling the optimisation routine's convergence precision and the step size for its numerical derivatives. That is tuning access for users whose series were not converging well under the defaults, and it is the only user-facing surface change visible here. The earlier entry even appears under a different package name, rjd3xhighfreq, which suggests some instability in how this line is published.

◆ Prediction

Expect further releases tracking JDemetra+ .jar versions, with R-level parameters exposed only as specific estimation problems surface; the entries do not support a firmer read than that.

Alternatives to ggstatsplot and rjd3highfreq

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 rjd3highfreq.

See all ggstatsplot alternatives → · See all rjd3highfreq alternatives →

Recent activity from ggstatsplot and rjd3highfreq

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

  1. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  2. 3mo agorjd3highfreqOptimisation precision and derivative step exposed on airline decomposition
  3. 4mo agoggstatsplotInternal maintenance only
  4. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  5. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  6. 8mo agorjd3highfreqrjd3highfreq 2.4.0
  7. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  8. 11mo agoggstatsplotAdapted to the latest ggplot2 release
  9. 1y agorjd3highfreqrjd3xhighfreq 2.3.0

Frequently asked questions

What is the difference between ggstatsplot and rjd3highfreq?

Both compete on the same themes — r-package — within Analytics. ggstatsplot and rjd3highfreq 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 rjd3highfreq?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstatsplot and rjd3highfreq 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 rjd3highfreq?

Top rjd3highfreq alternatives in Analytics are ranked by recent ship velocity. Browse the "rjd3highfreq alternatives" section above for the current picks, or visit /alternatives/rjd3highfreq for the full list with editorial commentary on each.