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distributional vs tern.rbmi

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

distributional vs tern.rbmi: at a glance

Featuredistributionaltern.rbmi
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, probability-distributions, distribution-arithmetic, numerical-methodspharmaverse, multiple-imputation, cran-maintenance, tabulation
Last editorial update6h 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 tern.rbmi?

Reference-based multiple imputation tables, shipping only what CRAN checks demand.

tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window, and the three older entries now backfilled are version-bump automation.

Read the full tern.rbmi trajectory →

distributional vs tern.rbmi: 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.

T
tern.rbmi
ANALYTICS
0.0

Reference-based multiple imputation tables, shipping only what CRAN checks demand.

◆ Current state

tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window, and the three older entries now backfilled are version-bump automation.

◆ Where it's heading

This is a thin adapter package and behaves like one — it moves when CRAN or an upstream dependency forces it to. Between 2022 and 2024 the feed shows only version bumps, and the 2025 releases are packaging concerns rather than analysis changes. The newly surfaced 2022 entries reinforce rather than change that reading.

◆ Prediction

Expect the next release to be triggered by a CRAN check failure or an {rbmi} update rather than by new tabulation features.

Alternatives to distributional and tern.rbmi

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 tern.rbmi.

See all distributional alternatives → · See all tern.rbmi alternatives →

Recent activity from distributional and tern.rbmi

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 agotern.rbmiVignette built only under gcc
  7. 1y agotern.rbmiV8 added to Suggests
  8. 1y agotern.rbmiCRAN resubmission with dependency and workflow updates
  9. 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
  10. 3y agotern.rbmiAutomated release commit for 0.1.1
  11. 4y agotern.rbmiDevelopment version bump to 0.1.0.9004
  12. 4y agotern.rbmiCI automation commit, no release content

Frequently asked questions

What is the difference between distributional and tern.rbmi?

They serve adjacent needs but don't currently overlap on shipped themes. distributional and tern.rbmi 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 tern.rbmi?

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

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