ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A side-by-side editorial comparison of fect and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
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.
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.
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.
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.
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.
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 fect or sdsfun.
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.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
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.
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.