STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of ecotraj and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
Ecological trajectory analysis builds out its cyclical branch, largely through one contributor
ecotraj analyses ecological community trajectories through multivariate space, and since 1.0.0 has carried cyclical ecological trajectory analysis (CETA) alongside the linear methods. Recent releases add convergence plotting, cycle shift arrows, correspondence and reduced major axis functions, and now trajectory averaging — most credited to a single contributor, N. Djeghri. Several older release notes are bare pointers to NEWS rather than descriptions.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
ecotraj analyses ecological community trajectories through multivariate space, and since 1.0.0 has carried cyclical ecological trajectory analysis (CETA) alongside the linear methods. Recent releases add convergence plotting, cycle shift arrows, correspondence and reduced major axis functions, and now trajectory averaging — most credited to a single contributor, N. Djeghri. Several older release notes are bare pointers to NEWS rather than descriptions.
The centre of gravity has shifted to cycles. The 1.0.0 release introduced CETA and reworked the underlying data structures for it, and every release since extends the cyclical branch or teaches an existing function to handle cycle objects — trajectoryDistances now compares cycles using dates for time comparison, and averageTrajectories covers both trajectories and cycles. A dependency on the MannKendall package was dropped in favour of base cor.test, trimming the install footprint.
The pattern of teaching existing linear-trajectory functions to accept cycle objects has repeated across several releases, so further functions gaining cycle support is the most grounded expectation.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
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 ecotraj or sdsfun.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all ecotraj alternatives → · See all sdsfun alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. ecotraj and sdsfun 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. ecotraj and sdsfun 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 ecotraj alternatives in Analytics are ranked by recent ship velocity. Browse the "ecotraj alternatives" section above for the current picks, or visit /alternatives/ecotraj for the full list with editorial commentary on each.
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.