EvoPhylo
EvoPhylo added BEAST2 alongside MrBayes, then went quiet for two years.
Comparison · Analytics
distributional vs epikit
A side-by-side editorial comparison of distributional and epikit — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
distributional vs epikit: at a glance
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.
What is epikit?
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.
distributional vs epikit: editorial side-by-side
distributional
0.0ANALYTICS
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.
epikit
0.0ANALYTICS
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
◆ Current state
epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.
◆ Where it's heading
The package is being scoped down rather than built out. The 0.1.3 restructuring and the 0.2.0 handover of proportions to epitabulate are the same move made twice: push functionality into the package where it belongs and keep epikit to the toolkit that field epidemiologists reach for directly. The rest of the history is dependency compatibility work against dplyr and tibble.
◆ Prediction
With proportions gone and dependencies trimmed, the remaining functions cluster tightly around dates and age bands, so further refinement of the date-reconstruction helpers is more likely than new capability areas.
Alternatives to distributional and epikit
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 epikit.
treespace
treespace ships once every year or two, and only when CRAN or a user forces it.
Rpath
Rpath 1.1.0 learns to read Ecopath's own files, easing migration off the desktop tool.
TAF
TAF keeps turning ICES stock assessments into reproducible, dependency-pinned projects.
parallelDist
parallelDist is in pure preservation mode — one build fix every few years.
cairo
Cairo finally catches R's graphics engine, all the way to GE API 16.
See all distributional alternatives → · See all epikit alternatives →
Recent activity from distributional and epikit
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
- 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators ⚡
- 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
- 5mo agodistributionalDirichlet and Horseshoe distributions added
- 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
- 9mo agoepikitProportion functions moved to epitabulate; date helpers warn correctly
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
- 3y agoepikitFunctions rearranged across sibling packages
- 5y agoepikitRaise dplyr and tibble minimums; move CI to GitHub Actions
- 5y agoepikitCompatibility release for dplyr 1.0.0
- 6y agoepikitFirst CRAN release
Frequently asked questions
What is the difference between distributional and epikit?
Both compete on the same themes — r-package — within Analytics. distributional and epikit 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 epikit?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributional and epikit 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 epikit?
Top epikit alternatives in Analytics are ranked by recent ship velocity. Browse the "epikit alternatives" section above for the current picks, or visit /alternatives/epikit-r for the full list with editorial commentary on each.