rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of icesSAG and weird — release velocity, themes, recent moves, and the top alternatives to consider.
The ICES stock assessment client took upload away in 2024 and spent two years giving it back.
icesSAG is the R client for the ICES Stock Assessment Graphs database, used by fisheries scientists to retrieve and publish stock assessment summaries and figures. The 1.5.0 release repointed every function at a new API, replaced token authentication with JWT via icesConnect, and dropped file upload entirely. Upload returned in 1.6.2, now routing through icesDatsu to check file format and validate data before submission.
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.
icesSAG is the R client for the ICES Stock Assessment Graphs database, used by fisheries scientists to retrieve and publish stock assessment summaries and figures. The 1.5.0 release repointed every function at a new API, replaced token authentication with JWT via icesConnect, and dropped file upload entirely. Upload returned in 1.6.2, now routing through icesDatsu to check file format and validate data before submission.
The package is consolidating onto the shared ices-tools stack rather than carrying its own machinery — authentication moved to icesConnect, validation to icesDatsu, and the icesVocab dependency was dropped once it was no longer needed. Alongside that, redundant graph functions were deprecated and caching was added to reduce load on the server. Releases are infrequent and driven by upstream API changes.
Expect the next release to follow whatever the ICES service or the sibling ices-tools packages change next, rather than introducing new analysis capability of its own.
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.
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.
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.
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 icesSAG or weird.
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all icesSAG alternatives → · See all weird alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. icesSAG 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. icesSAG 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.
Top icesSAG alternatives in Analytics are ranked by recent ship velocity. Browse the "icesSAG alternatives" section above for the current picks, or visit /alternatives/icessag for the full list with editorial commentary on each.
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.