EvoPhylo
EvoPhylo added BEAST2 alongside MrBayes, then went quiet for two years.
Comparison · Analytics
mutagen vs weird
A side-by-side editorial comparison of mutagen and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
mutagen vs weird: at a glance
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.
What is weird?
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
mutagen vs weird: editorial side-by-side
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.
weird
0.0ANALYTICS
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
◆ Current state
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
◆ Where it's heading
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
◆ Prediction
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
Alternatives to mutagen and weird
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 mutagen or weird.
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 mutagen alternatives → · See all weird alternatives →
Recent activity from mutagen and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 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
- 2y agoweirdWine reviews dataset replaced with a fetch function
Frequently asked questions
What is the difference between mutagen and weird?
Both compete on the same themes — r-package — within Analytics. mutagen and weird 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 mutagen better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mutagen and weird 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 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.
What are the best alternatives to weird?
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.