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distributional vs ggdemetra

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

distributional vs ggdemetra: at a glance

Featuredistributionalggdemetra
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, probability-distributions, distribution-arithmetic, numerical-methodsseasonal-adjustment, ggplot2, time-series, tramo-seats
Last editorial update7h ago1h ago
WebsiteVisit →Visit →

What is distributional?

distributional taught + and - to work on any pair of distributions, closing the algebra it started with.

The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.

Read the full distributional trajectory →

What is ggdemetra?

A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.

ggdemetra is a thin, focused bridge: it puts RJDemetra's seasonal adjustment results — TRAMO-SEATS and X-13 models — into ggplot2 geoms and autoplot methods. Development runs in short bursts separated by long quiet stretches, and the most recent work has been correcting SI ratio handling rather than adding surface. The API is small enough that a single function rename counts as the notable change in a release.

Read the full ggdemetra trajectory →

distributional vs ggdemetra: editorial side-by-side

D0.0

distributional taught + and - to work on any pair of distributions, closing the algebra it started with.

◆ Current state

The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.

◆ Where it's heading

The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.

◆ Prediction

Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.

G
ggdemetra
ANALYTICS
0.0

A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.

◆ Current state

ggdemetra is a thin, focused bridge: it puts RJDemetra's seasonal adjustment results — TRAMO-SEATS and X-13 models — into ggplot2 geoms and autoplot methods. Development runs in short bursts separated by long quiet stretches, and the most recent work has been correcting SI ratio handling rather than adding surface. The API is small enough that a single function rename counts as the notable change in a release.

◆ Where it's heading

The package has been steadily completing its coverage of the seasonal adjustment output surface: component extractors and autoplot methods in 0.2.3, SI ratio plotting in 0.2.5, then two releases of corrections to make SI ratios behave under TRAMO-SEATS jSA models and when no seasonal component is exported. Alongside that, the naming is being tidied — y_forecast() became raw(), and init_ggplot() shortened the setup boilerplate. This reads as a package approaching the edge of its intended scope and spending its effort on correctness.

◆ Prediction

Two consecutive releases fixing SI ratios under TRAMO-SEATS suggest that code path is the least settled part of the package, so further corrections there are the most likely next move. The entries give no indication of new model families or plot types being planned.

Alternatives to distributional and ggdemetra

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 distributional or ggdemetra.

See all distributional alternatives → · See all ggdemetra alternatives →

Recent activity from distributional and ggdemetra

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

  1. 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
  2. 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators
  3. 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
  4. 5mo agodistributionalDirichlet and Horseshoe distributions added
  5. 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
  6. 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
  7. 2y agoggdemetrasiratio() fix when TRAMO-SEATS exports no seasonal component
  8. 2y agoggdemetraraw() replaces y_forecast(); new init_ggplot() helper
  9. 2y agoggdemetraRe-tagged moments later as 0.2.7
  10. 3y agoggdemetraSI ratio plotting functions land
  11. 5y agoggdemetrats2df() conversion helper and geom_outlier date fix
  12. 6y agoggdemetrageom_arima no longer recomputes the model

Frequently asked questions

What is the difference between distributional and ggdemetra?

They serve adjacent needs but don't currently overlap on shipped themes. distributional and ggdemetra 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 distributional better than ggdemetra?

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

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

What are the best alternatives to ggdemetra?

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