EvoPhylo
EvoPhylo added BEAST2 alongside MrBayes, then went quiet for two years.
Comparison · Analytics
distributional vs mutagen
A side-by-side editorial comparison of distributional and mutagen — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
distributional vs mutagen: 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 mutagen?
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
mutagen provides row-wise column-generation helpers for R data frames in the spirit of Stata's egen — gen_rowmean(), gen_rowsum(), gen_rowsd(), gen_rownonmiss() and about a dozen siblings. It reached 0.5.0 within three months of its first release, adding two or three functions each time. The most recent release adds gen_coldiff() and renames two functions to fit the naming scheme.
distributional vs mutagen: 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.
mutagen
0.0ANALYTICS
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
◆ Current state
mutagen provides row-wise column-generation helpers for R data frames in the spirit of Stata's egen — gen_rowmean(), gen_rowsum(), gen_rowsd(), gen_rownonmiss() and about a dozen siblings. It reached 0.5.0 within three months of its first release, adding two or three functions each time. The most recent release adds gen_coldiff() and renames two functions to fit the naming scheme.
◆ Where it's heading
The package is filling out a known surface rather than discovering one: the reference implementation exists in Stata, so development is a matter of working through the list. Alongside that, the naming convention is still settling — gen_rowmatch became gen_rowany, gen_percent became gen_colpercent, gen_na_listcol became gen_listcol_na — which is normal for a pre-1.0 package but means callers should expect further renames. Contributions are arriving from several first-time contributors.
◆ Prediction
The gen_col* prefix has only two members against a dozen gen_row* functions, so column-wise coverage is the obvious gap; expect it to fill before the naming stabilises for a 1.0.
Alternatives to distributional and mutagen
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 mutagen.
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 mutagen alternatives →
Recent activity from distributional and mutagen
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
- 8mo agomutagengen_coldiff() added; two functions renamed for consistency
- 9mo agomutagengen_rowsum() and gen_rowsd() added
- 9mo agomutagengen_rownonmiss() and gen_rowall() added
- 9mo agomutagenRow mean, median and missingness helpers; gen_rowmatch renamed
- 11mo agomutagenFirst release with the row-wise gen_* family
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
Frequently asked questions
What is the difference between distributional and mutagen?
Both compete on the same themes — r-package — within Analytics. distributional and mutagen 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 mutagen?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributional and mutagen 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 mutagen?
Top mutagen alternatives in Analytics are ranked by recent ship velocity. Browse the "mutagen alternatives" section above for the current picks, or visit /alternatives/mutagen-r for the full list with editorial commentary on each.