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Comparison · Infra & APIs

ggdist vs rgm

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

Shared themes:r-package

ggdist vs rgm: at a glance

Featureggdistrgm
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesdata-visualization, uncertainty, bayesian-statistics, ggplot2microbiome, graphical-models, bayesian-inference, cran-maintenance
Last editorial update1d ago1h ago
WebsiteVisit →Visit →

What is ggdist?

The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.

ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.

Read the full ggdist trajectory →

What is rgm?

A microbiome network model that got itself un-archived by deleting the dependency that killed it.

rgm implements the random graphical model for microbiome interactions across related environments, published in JABES in 2026. The package was archived from CRAN in February 2026 because of its dependency on huge; the recovery release drops that dependency entirely, which cost it the graphical-lasso warm start that used to seed the initial graph — the default is now an empty graph, with warm starts left to the user. A post-processing function returning ggplot diagnostics arrived in the same release.

Read the full rgm trajectory →

ggdist vs rgm: editorial side-by-side

G
ggdist
INFRA · APIS
0.0

The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.

◆ Current state

ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.

◆ Where it's heading

Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.

◆ Prediction

Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.

R
rgm
INFRA · APIS
0.0

A microbiome network model that got itself un-archived by deleting the dependency that killed it.

◆ Current state

rgm implements the random graphical model for microbiome interactions across related environments, published in JABES in 2026. The package was archived from CRAN in February 2026 because of its dependency on huge; the recovery release drops that dependency entirely, which cost it the graphical-lasso warm start that used to seed the initial graph — the default is now an empty graph, with warm starts left to the user. A post-processing function returning ggplot diagnostics arrived in the same release.

◆ Where it's heading

Three tags shipped inside two hours on one day, and the notes are candid about why: 1.1.0 held the actual work but was never released, 1.2.0 restated it under a higher version to signal the size of the change, and 1.2.1 answered CRAN pre-test feedback. Beyond the archival recovery, the visible work is housekeeping that had accumulated — a shadowed rmvnorm() definition, roxygen import tags that were silently emitting nothing, leftover C++ template scaffolding, and build artifacts under version control. The diagnostics function is the only genuinely new user-facing capability in the window.

◆ Prediction

The immediate task was restoring availability, and that is done; the open question the entries raise is whether losing the graphical-lasso warm start affects convergence in practice, which the new diagnostic plots are positioned to answer.

Alternatives to ggdist and rgm

Other Infra & APIs 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 ggdist or rgm.

See all ggdist alternatives → · See all rgm alternatives →

Recent activity from ggdist and rgm

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

  1. 3mo agorgmJournal DOI replaces the preprint; promotional wording removed
  2. 3mo agorgmBack on CRAN after dropping the dependency that caused archival
  3. 3mo agorgmUnreleased twin of the CRAN recovery release
  4. 1y agoggdistPer-geometry thickness subscales and settable defaults
  5. 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator
  6. 2y agorgmFirst release: simulation, estimation and post-processing
  7. 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
  8. 3y agoggdistBounded density becomes the default; existing charts change
  9. 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
  10. 4y agoggdistComputed variables shared across sub-geometries

Frequently asked questions

What is the difference between ggdist and rgm?

Both compete on the same themes — r-package — within Infra & APIs. ggdist and rgm 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 ggdist better than rgm?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggdist and rgm 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to ggdist?

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

What are the best alternatives to rgm?

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