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sdsfun vs tEDM

A side-by-side editorial comparison of sdsfun and tEDM — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

sdsfun vs tEDM: at a glance

FeaturesdsfuntEDM
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesspatial-statistics, geodetector, spatial-clustering, rcppcausal-inference, time-series, empirical-dynamic-modeling, r-package
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is sdsfun?

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.

Read the full sdsfun trajectory →

What is tEDM?

The temporal half of the stscl EDM pair, tracking its spatial sibling

tEDM applies empirical dynamic modeling to time series — cross mapping, convergent cross mapping and the logistic map — as the temporal counterpart to spEDM, with which it shares a maintainer and a C++ core. The recent releases are consolidation rather than expansion: index handling in cross mapping corrected, generics taught to accept varying E, k and tau, and the associated paper now cited in the README. Only three releases are visible in the feed.

Read the full tEDM trajectory →

sdsfun vs tEDM: editorial side-by-side

S
sdsfun
ANALYTICS
0.0

A spatial-statistics utility package exists to be depended on, and is built accordingly.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

T
tEDM
ANALYTICS
0.0

The temporal half of the stscl EDM pair, tracking its spatial sibling

◆ Current state

tEDM applies empirical dynamic modeling to time series — cross mapping, convergent cross mapping and the logistic map — as the temporal counterpart to spEDM, with which it shares a maintainer and a C++ core. The recent releases are consolidation rather than expansion: index handling in cross mapping corrected, generics taught to accept varying E, k and tau, and the associated paper now cited in the README. Only three releases are visible in the feed.

◆ Where it's heading

tEDM moves in lockstep with spEDM. Configurable distance metrics, varying E/k/tau inputs, strict floating-point comparison and the S3 plotting font unification all appear in both packages within days or weeks, as does the maintainer surname correction. The recent balance has tilted toward correcting library and prediction index handling — the kind of repeated attention that suggests the indexing model was the weak point of the shared core.

◆ Prediction

Expect tEDM to keep inheriting the shared-core changes spEDM lands, with its own releases staying small and centred on cross-mapping parameter handling rather than new method surface.

Alternatives to sdsfun and tEDM

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 sdsfun or tEDM.

See all sdsfun alternatives → · See all tEDM alternatives →

Recent activity from sdsfun and tEDM

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 4mo agotEDMMaintainer name corrected, published paper cited
  2. 7mo agotEDMCross-mapping index handling corrected, generics accept varying E, k, tau
  3. 10mo agosdsfunPackage load stops touching the RNG state
  4. 11mo agotEDMConfigurable distance metrics for cross mapping
  5. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  6. 1y agosdsfunMissing-value handling added to linear trend removal
  7. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  8. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  9. 1y agosdsfunFast geodetector q-value estimator added

Frequently asked questions

What is the difference between sdsfun and tEDM?

Both compete on the same themes — r-package — within Analytics. sdsfun and tEDM 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 sdsfun better than tEDM?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. sdsfun and tEDM 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 sdsfun?

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.

What are the best alternatives to tEDM?

Top tEDM alternatives in Analytics are ranked by recent ship velocity. Browse the "tEDM alternatives" section above for the current picks, or visit /alternatives/tedm for the full list with editorial commentary on each.