qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
distributional vs symengine
A side-by-side editorial comparison of distributional and symengine — release velocity, themes, recent moves, and the top alternatives to consider.
distributional vs symengine: 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 symengine?
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
symengine gives R access to the SymEngine computer algebra core for symbolic expressions, matrices and sets. The tracked feed carries the upstream C++ library's releases rather than R-binding changes, so what shows here is core work: parser fixes, locale-independent double parsing, an SOVERSION bump and matrix transpose corrections. Feature growth in the core has slowed considerably since the 0.9 and 0.10 releases.
distributional vs symengine: 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.
symengine
0.0ANALYTICS
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
◆ Current state
symengine gives R access to the SymEngine computer algebra core for symbolic expressions, matrices and sets. The tracked feed carries the upstream C++ library's releases rather than R-binding changes, so what shows here is core work: parser fixes, locale-independent double parsing, an SOVERSION bump and matrix transpose corrections. Feature growth in the core has slowed considerably since the 0.9 and 0.10 releases.
◆ Where it's heading
The upstream core has moved from adding capability — serialization, a first simplify(), set types, matrix expressions, LLVM support — toward maintenance: build fixes, dependency support such as Flint3, and correctness patches. For R users the practical consequence is that new symbolic features arrive only as fast as the binding exposes them, which this feed does not report on.
◆ Prediction
Expect further upstream maintenance releases tracking LLVM and Flint versions; nothing in these notes signals a new capability push.
Alternatives to distributional and symengine
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 symengine.
constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all distributional alternatives → · See all symengine alternatives →
Recent activity from distributional and symengine
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 agosymengineLocale-independent double parsing and matrix transpose fix
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
- 2y agosymengineFlint3 support and SBML printing fixes
- 3y agosymengineBuild fixes only, no functional change
- 3y agosymengineMatrix expressions, Intersection class and LLVM 16 support
- 4y agosymengineAdds serialization and a first simplify() implementation
- 4y agosymengineFixes MSVC2017 compilation failure
Frequently asked questions
What is the difference between distributional and symengine?
They serve adjacent needs but don't currently overlap on shipped themes. distributional and symengine 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 symengine?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributional and symengine 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 symengine?
Top symengine alternatives in Analytics are ranked by recent ship velocity. Browse the "symengine alternatives" section above for the current picks, or visit /alternatives/symengine-r for the full list with editorial commentary on each.