rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
vegan vs weird
A side-by-side editorial comparison of vegan and weird — release velocity, themes, recent moves, and the top alternatives to consider.
vegan vs weird: at a glance
What is vegan?
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
vegan is the reference R package for ordination and diversity analysis in community ecology. The 2.7 line redesigned constrained ordination graphics from scratch, made adonis defunct in favor of adonis2, and moved permutation tests for partial RDA and db-RDA onto residualized predictors. The current 2.7-5 release is stabilization — parallel processing on Windows, ggvegan compatibility for tidy scores, and arrow label placement.
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.
vegan vs weird: editorial side-by-side
vegan
0.0ANALYTICS
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
◆ Current state
vegan is the reference R package for ordination and diversity analysis in community ecology. The 2.7 line redesigned constrained ordination graphics from scratch, made adonis defunct in favor of adonis2, and moved permutation tests for partial RDA and db-RDA onto residualized predictors. The current 2.7-5 release is stabilization — parallel processing on Windows, ggvegan compatibility for tidy scores, and arrow label placement.
◆ Where it's heading
Two long deprecation programs are converging. Plotting is being pushed out of the package: lattice functions are deprecated in favor of ggplot2 equivalents now living in ggvegan, a separate CRAN package, while vegan's own base graphics were rebuilt around independently configurable score types and pipe-based construction. Meanwhile the statistical core is being made internally consistent — add1 and drop1 no longer use different internal models, and summary is no longer an accepted route to ordination scores.
◆ Prediction
Expect the remaining lattice functions to go defunct and more plotting responsibility to shift to ggvegan, leaving vegan as the statistical engine with a thin base graphics layer.
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 vegan 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 vegan or weird.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
Recent activity from vegan and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 2mo agoveganParallel processing stabilized, especially on Windows
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 5mo agoveganLattice plotting deprecated as ggvegan reaches CRAN
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 10mo agoveganPartial RDA permutation tests adopt residualized predictors
- 1y agoveganOrdination graphics rebuilt and adonis made defunct ⚡
- 1y agoveganRelease chasing undefined behavior in a C function
- 1y agoveganpca, ca and pco added for unconstrained ordination
- 2y agoweirdWine reviews dataset replaced with a fetch function
Frequently asked questions
What is the difference between vegan and weird?
They serve adjacent needs but don't currently overlap on shipped themes. vegan 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 vegan better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. vegan 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 vegan?
Top vegan alternatives in Analytics are ranked by recent ship velocity. Browse the "vegan alternatives" section above for the current picks, or visit /alternatives/vegan-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.