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broman vs distributional

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

Shared themes:r-package

broman vs distributional: at a glance

Featurebromandistributional
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstatistics, base-graphics, utilities, r-packager-package, probability-distributions, distribution-arithmetic, numerical-methods
Last editorial update58m ago3h ago
WebsiteVisit →Visit →

What is broman?

A statistician's personal toolbox, growing one plotting utility at a time

broman is Karl Broman's collection of personal R utilities — base-graphics plotting helpers such as grayplot, dotplot and timeplot, running-window summaries, and assorted conveniences. Recent releases alternate between small additions, like runningratio2() with an adaptive window sized to hit a target denominator, and narrow bug fixes in crayons() and jiggle(). Version 0.92 removes an include that had begun warning on CRAN.

Read the full broman trajectory →

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 →

broman vs distributional: editorial side-by-side

B
broman
ANALYTICS
0.0

A statistician's personal toolbox, growing one plotting utility at a time

◆ Current state

broman is Karl Broman's collection of personal R utilities — base-graphics plotting helpers such as grayplot, dotplot and timeplot, running-window summaries, and assorted conveniences. Recent releases alternate between small additions, like runningratio2() with an adaptive window sized to hit a target denominator, and narrow bug fixes in crayons() and jiggle(). Version 0.92 removes an include that had begun warning on CRAN.

◆ Where it's heading

The additions cluster around two themes: time-axis plotting and running-window summaries, both of which have been extended across several releases. Nothing here is planned in the usual sense — functions appear when the author needs them and bugs are fixed when they surface downstream, as jiggle() did through dotplot(). The C-level cleanup in 0.92 matches the same change made to R/qtl the same week, which is what maintaining a set of packages under one author looks like.

◆ Prediction

Both recent function additions extend existing families rather than starting new ones, so the next release is most likely another variant in the running-window or time-plotting group, or a fix surfaced by one of the author's other packages.

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.

Alternatives to broman and distributional

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 broman or distributional.

See all broman alternatives → · See all distributional alternatives →

Recent activity from broman and distributional

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. 8mo agobromanRemove R_ext/PrtUtil.h include flagged by CRAN
  7. 10mo agobromanFix exact-name matching in crayons()
  8. 11mo agobromanFix jiggle() with factors missing levels
  9. 1y agobromanrunningratio2() uses an adaptive window
  10. 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
  11. 2y agobromantimeplot() added; running functions accept NAs
  12. 2y agobromantime_axis() added for date-time axis labels

Frequently asked questions

What is the difference between broman and distributional?

Both compete on the same themes — r-package — within Analytics. broman and distributional 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 broman better than distributional?

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

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

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.