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sdsfun vs slope

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

Shared themes:r-package

sdsfun vs slope: at a glance

Featuresdsfunslope
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesspatial-statistics, geodetector, spatial-clustering, rcppsparse-regression, penalized-models, cpp, r-package
Last editorial update1h ago6h 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 slope?

A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface

SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.

Read the full slope trajectory →

sdsfun vs slope: 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.

S
slope
ANALYTICS
0.0

A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface

◆ Current state

SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.

◆ Where it's heading

The arc runs rewrite, then repair, then convenience. The 1.2.0 release is the repair phase — coefficients_scaled was returning unscaled values, which silently affected every coef.SLOPE() call — and 2.0.0 onward is convenience, with refit() now working without re-supplying training data. The tag timestamps are non-monotonic: 1.0.1 is stamped a minute after 1.1.0 despite the lower version, so ordering here reflects when tags were pushed, not what superseded what.

◆ Prediction

With the cross-validation workflow now closing itself out through automatic refitting, further work is more likely to extend the summary and plotting surface than to touch the solver again.

Alternatives to sdsfun and slope

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 slope.

See all sdsfun alternatives → · See all slope alternatives →

Recent activity from sdsfun and slope

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

  1. 2mo agosloperefit() defaults to training data; class-mismatch scoring fixed
  2. 6mo agoslopeCross-validation now refits automatically and gains summary methods
  3. 9mo agoslopeSingle-threaded by default, interruptible, and a scaling bug fixed
  4. 9mo agoslopeM1 Mac test fix
  5. 9mo agoslopeGlioma gene expression dataset added
  6. 10mo agosdsfunPackage load stops touching the RNG state
  7. 1y agoslopeSLOPE 1.0.0
  8. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  9. 1y agosdsfunMissing-value handling added to linear trend removal
  10. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  11. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  12. 1y agosdsfunFast geodetector q-value estimator added

Frequently asked questions

What is the difference between sdsfun and slope?

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

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

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