tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
Comparison · Analytics
distributional vs geodist
A side-by-side editorial comparison of distributional and geodist — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
distributional vs geodist: 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 geodist?
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
geodist computes geodesic distances between coordinate pairs in C with no dependencies, offering several measures that trade accuracy for speed — including a 'cheap' approximation used by default. The API is small and largely finished; 0.1.0 added geodist_min() for nearest-match lookups and 0.1.1 is a compiler warning fix.
distributional vs geodist: 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.
geodist
0.0ANALYTICS
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
◆ Current state
geodist computes geodesic distances between coordinate pairs in C with no dependencies, offering several measures that trade accuracy for speed — including a 'cheap' approximation used by default. The API is small and largely finished; 0.1.0 added geodist_min() for nearest-match lookups and 0.1.1 is a compiler warning fix.
◆ Where it's heading
Development has been about making the speed-accuracy trade visible rather than hiding it. The 0.0.6 release added messages telling users to pick a different measure once the default cheap approximation is applied beyond 100km, where its error stops being negligible. Around that, the work is input handling — tibble support, better lon/lat column matching, vector inputs — and hardening the C code. It is a package that treats being small and correct as the feature.
◆ Prediction
Expect continued low-frequency maintenance: compiler warnings and geodesic source updates account for three of the last six releases, and the function surface has grown by only two entries in five years.
Alternatives to distributional and geodist
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 geodist.
tern.mmrm
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
ggmagnify
A single-purpose ggplot2 inset tool, refining the same three arguments.
symengine
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
gtfstools
gtfstools stopped guarding its own object model and started accepting everyone else's.
quantities
The glue package that makes R carry units and uncertainty through the same calculation.
See all distributional alternatives → · See all geodist alternatives →
Recent activity from distributional and geodist
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
- 1y agogeodistgeodist 0.1.1 clears a clang warning in geodesic.c
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
- 2y agogeodistgeodist 0.1.0 adds geodist_min() for nearest matches
- 3y agogeodistgeodist 0.0.8 updates geodesic source, fixes clang warnings
- 5y agogeodistgeodist 0.0.7 improves lon/lat column matching and tibbles
- 5y agogeodistgeodist 0.0.6 warns when cheap distances exceed 100km
- 6y agogeodistgeodist 0.0.4 adds geodist_vec() for vector inputs
Frequently asked questions
What is the difference between distributional and geodist?
Both compete on the same themes — r-package — within Analytics. distributional and geodist 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 geodist?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributional and geodist 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 geodist?
Top geodist alternatives in Analytics are ranked by recent ship velocity. Browse the "geodist alternatives" section above for the current picks, or visit /alternatives/geodist-r for the full list with editorial commentary on each.