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fect vs sdsfun

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

Shared themes:r-package

fect vs sdsfun: at a glance

Featurefectsdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, causal-inference, panel-data, api-redesignspatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is fect?

A counterfactual estimator turning itself into a platform for multiple estimands

fect implements counterfactual estimators for panel data with treatment effects — imputation-based fixed effects, interactive fixed effects, matrix completion. The 2026 releases move fast and bundle heavily: 2.1.0 rewrote complex fixed effect handling, 2.2.0 unified cross-validation under a single cv.method parameter and replaced method='gsynth' with an explicit time.component.from switch, 2.4.1 introduced a post-hoc estimand API, and 2.4.5 added group.fe for coarsened fixed effects plus a $sample slot exposing which cells entered estimation.

Read the full fect 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 →

fect vs sdsfun: editorial side-by-side

F
fect
ANALYTICS
0.0

A counterfactual estimator turning itself into a platform for multiple estimands

◆ Current state

fect implements counterfactual estimators for panel data with treatment effects — imputation-based fixed effects, interactive fixed effects, matrix completion. The 2026 releases move fast and bundle heavily: 2.1.0 rewrote complex fixed effect handling, 2.2.0 unified cross-validation under a single cv.method parameter and replaced method='gsynth' with an explicit time.component.from switch, 2.4.1 introduced a post-hoc estimand API, and 2.4.5 added group.fe for coarsened fixed effects plus a $sample slot exposing which cells entered estimation.

◆ Where it's heading

The direction is separation of estimation from interpretation. Where the package once returned one effect from one fit, estimand() now dispatches typed estimands — ATT, cumulative ATT, APTT, log ATT — from any imputation fit, with effect() and att.cumu() soft-deprecated but byte-identical pending 3.0.0. Alongside that runs a transparency thread: the $sample matrix, out-of-sample comparison via fect_mspe(), and named component sources instead of opaque method aliases. The release notes are unusually precise about which results change and which do not.

◆ Prediction

The soft-deprecation notice names 3.0.0 as the removal point for effect() and att.cumu(), so a major release consolidating on the estimand() dispatcher is the clearly signposted next step.

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 fect 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 fect or sdsfun.

See all fect alternatives → · See all sdsfun alternatives →

Recent activity from fect and sdsfun

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

  1. 2mo agofectAdds group.fe for coarsened fixed effects and a $sample slot
  2. 3mo agofectPost-hoc estimand API decouples estimands from the fit
  3. 4mo agofectUnified cross-validation and explicit control of time components
  4. 7mo agofectRewrites complex fixed effect handling and fixes speed
  5. 10mo agosdsfunPackage load stops touching the RNG state
  6. 11mo agofectAdds heterogeneous treatment effect plots and caps default cores
  7. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  8. 1y agosdsfunMissing-value handling added to linear trend removal
  9. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  10. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  11. 1y agosdsfunFast geodetector q-value estimator added

Frequently asked questions

What is the difference between fect and sdsfun?

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

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

Top fect alternatives in Analytics are ranked by recent ship velocity. Browse the "fect alternatives" section above for the current picks, or visit /alternatives/fect 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.