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distributional vs epiworldR

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

Shared themes:r-package

distributional vs epiworldR: at a glance

FeaturedistributionalepiworldR
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, probability-distributions, distribution-arithmetic, numerical-methodsr-package, epidemiology, agent-based-simulation, cran
Last editorial update2h 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 epiworldR?

epiworldR is a thin R shell whose releases track the C++ simulator underneath it

Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.

Read the full epiworldR trajectory →

distributional vs epiworldR: 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.

E
epiworldR
ANALYTICS
0.0

epiworldR is a thin R shell whose releases track the C++ simulator underneath it

◆ Current state

Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.

◆ Where it's heading

The R package's job is staying current with the simulator and satisfying CRAN, not evolving its own interface. What direction it has shows in which model outputs get exposed next, and in a steady tidy-up of the build — the custom configure script was dropped in favour of R's built-in C++17 and OpenMP settings, and test coverage has been filled in across several releases with automated assistance.

◆ Prediction

Expect the next release to track another epiworld version bump, with any R-side addition most likely being one more exposed metric or saver, following the pattern of get_hospitalizations and get_outbreak_size.

Alternatives to distributional and epiworldR

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 epiworldR.

See all distributional alternatives → · See all epiworldR alternatives →

Recent activity from distributional and epiworldR

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. 4mo agoepiworldR0.14.0 addresses an AddressSanitizer finding
  5. 5mo agodistributionalDirichlet and Horseshoe distributions added
  6. 5mo agoepiworldRWrapper bumped to track a new epiworld version
  7. 5mo agoepiworldRBuild drops the custom configure script for R's C++17 and OpenMP settings
  8. 6mo agoepiworldRepiworld bumped to 0.11.2
  9. 7mo agoepiworldRTests updated at CRAN's request
  10. 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
  11. 7mo agoepiworldRHospitalizations, outbreak size and active cases exposed to R
  12. 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families

Frequently asked questions

What is the difference between distributional and epiworldR?

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

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

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