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probmed vs sdsfun

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

probmed vs sdsfun: at a glance

Featureprobmedsdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themescausal mediation, effect size, semiparametric inference, cross-fittingspatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update6h ago45m ago
WebsiteVisit →Visit →

What is probmed?

probmed went from one probabilistic effect size to a family of them in sixteen days.

probmed computes P_med, a scale-free probabilistic effect size for causal mediation, as part of the Data-Wise mediationverse alongside medfit, medsim and RMediation. Three releases in three weeks took it from a single estimator to four additional families built on a shared cross-fitted corner-EIF core, covering gauge-calibrated, incremental-elasticity and Sobol variance-share versions of the proportion mediated. Distribution is GitHub and r-universe rather than CRAN, with a load-bearing Remotes pin on medfit.

Read the full probmed trajectory →

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 →

probmed vs sdsfun: editorial side-by-side

P
probmed
ANALYTICS
0.0

probmed went from one probabilistic effect size to a family of them in sixteen days.

◆ Current state

probmed computes P_med, a scale-free probabilistic effect size for causal mediation, as part of the Data-Wise mediationverse alongside medfit, medsim and RMediation. Three releases in three weeks took it from a single estimator to four additional families built on a shared cross-fitted corner-EIF core, covering gauge-calibrated, incremental-elasticity and Sobol variance-share versions of the proportion mediated. Distribution is GitHub and r-universe rather than CRAN, with a load-bearing Remotes pin on medfit.

◆ Where it's heading

The pace is manuscript-driven — estimators arrive with their citations attached and vignettes alongside, and the 0.1.0 notes correct the estimand itself against a manuscript definition rather than fixing a bug in code. Each release adds inference machinery as well as point estimates: percentile-bootstrap intervals and Fieller sets in 0.3.0, a deterministic MBCO interval in 0.2.0 that avoids resampling entirely. The gauge residual and the pmed_sensitivity() helper suggest a growing concern with when the estimand does not decompose at all.

◆ Prediction

0.3.0 shipped a sensitivity helper for shared mediator-outcome confounding and a diagnostic that flags non-decomposability, so the next release most likely extends that diagnostic side rather than adding a fifth estimator family.

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.

Alternatives to probmed and sdsfun

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 probmed or sdsfun.

See all probmed alternatives → · See all sdsfun alternatives →

Recent activity from probmed and sdsfun

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

  1. 1mo agoprobmedFour estimator families on a cross-fitted corner-EIF core
  2. 2mo agoprobmedParallel mediators and a resampling-free MBCO interval
  3. 2mo agoprobmedFirst release: pmed() with the estimand corrected
  4. 10mo agosdsfunPackage load stops touching the RNG state
  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 probmed and sdsfun?

They serve adjacent needs but don't currently overlap on shipped themes. probmed 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.

Is probmed better than sdsfun?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. probmed 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.

What are the best alternatives to probmed?

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

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.