tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
Comparison · Analytics
distributional vs paleobuddy
A side-by-side editorial comparison of distributional and paleobuddy — release velocity, themes, recent moves, and the top alternatives to consider.
distributional vs paleobuddy: 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 paleobuddy?
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
paleobuddy simulates diversification, fossil records and phylogenetic trees, with rates that can be arbitrary functions of time — its founding idea, implemented through rexp.var() generalizing exponential and Weibull draws. The 1.1.0 release adds state-dependent speciation and extinction simulation at roughly MuHiSSE generality, and lets simulations stop at a target number of extant species instead of conditioning on time.
distributional vs paleobuddy: 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.
paleobuddy
0.0ANALYTICS
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
◆ Current state
paleobuddy simulates diversification, fossil records and phylogenetic trees, with rates that can be arbitrary functions of time — its founding idea, implemented through rexp.var() generalizing exponential and Weibull draws. The 1.1.0 release adds state-dependent speciation and extinction simulation at roughly MuHiSSE generality, and lets simulations stop at a target number of extant species instead of conditioning on time.
◆ Where it's heading
Releases track the maintainer's publications rather than a product cadence — 1.0.0 accompanied the MEE manuscript, 1.0.0.1 exists purely as a Zenodo citation anchor, and 1.1.0 is stated as going with a paper on SSE model accuracy for trees including fossil data. That framing sets the direction: the package grows whichever capability the next study needs to test. The stated SSE limits, no quantitative traits and no cladogenetic transitions, mark exactly where that boundary currently sits.
◆ Prediction
Quantitative traits and cladogenetic transitions are named as missing, which makes them the obvious next targets, though on this history the timing will follow a paper rather than a roadmap.
Alternatives to distributional and paleobuddy
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 paleobuddy.
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 paleobuddy alternatives →
Recent activity from distributional and paleobuddy
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 agopaleobuddypaleobuddy 1.1.0 adds SSE trait-dependent simulation ⚡
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
- 3y agopaleobuddypaleobuddy 1.0.0.1: Zenodo citation release
- 4y agopaleobuddypaleobuddy 1.0.0: first release with time-varying rates
Frequently asked questions
What is the difference between distributional and paleobuddy?
They serve adjacent needs but don't currently overlap on shipped themes. distributional and paleobuddy 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 paleobuddy?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributional and paleobuddy 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 paleobuddy?
Top paleobuddy alternatives in Analytics are ranked by recent ship velocity. Browse the "paleobuddy alternatives" section above for the current picks, or visit /alternatives/paleobuddy for the full list with editorial commentary on each.