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kernelshap vs spatstat

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

kernelshap vs spatstat: at a glance

Featurekernelshapspatstat
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessspatial-statistics, r-package, metapackage, documentation
Last editorial update42m ago1h ago
WebsiteVisit →Visit →

What is kernelshap?

kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.

kernelshap computes model-agnostic SHAP values in R through Kernel SHAP, permutation SHAP and an exact additive explainer. Version 0.8.0 added a sampling permutation-SHAP algorithm with standard errors and early stopping, lifting the practical feature ceiling past what the exact method allows. Version 0.9.0 then corrected a bug in how kernel weights were computed — exact Kernel SHAP now agrees with exact permutation SHAP — and moved parallelism from foreach to doFuture.

Read the full kernelshap trajectory →

What is spatstat?

The spatstat umbrella package, now mostly a pointer to the sub-packages doing the work

spatstat is the front package of a family that was split into specialised components — spatstat.geom, spatstat.random, spatstat.model, spatstat.explore, spatstat.univar and spatstat.sparse. Its own release notes reflect that: entries in this window are largely announcements of where the real changes landed, plus documentation and cross-reference maintenance. The codebase it fronts passed 200,000 lines as of 3.5-1.

Read the full spatstat trajectory →

kernelshap vs spatstat: editorial side-by-side

K
kernelshap
ANALYTICS
0.0

kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.

◆ Current state

kernelshap computes model-agnostic SHAP values in R through Kernel SHAP, permutation SHAP and an exact additive explainer. Version 0.8.0 added a sampling permutation-SHAP algorithm with standard errors and early stopping, lifting the practical feature ceiling past what the exact method allows. Version 0.9.0 then corrected a bug in how kernel weights were computed — exact Kernel SHAP now agrees with exact permutation SHAP — and moved parallelism from foreach to doFuture.

◆ Where it's heading

Two concerns drive this package: making exact methods reach further, and being demonstrably right. The first shows in the additive explainer, the optional background dataset and the sampling permutation algorithm; the second in unit tests written against Python's shap, credited fixes from outside contributors, and a willingness to ship a correctness fix that changes numbers people have already published. Speed work runs continuously underneath — direct solves replacing the Moore-Penrose pseudo-inverse, roughly 10% less memory.

◆ Prediction

The 0.6.0 and 0.7.0 notes each promised a stable 1.0.0 that has not arrived; with the weighting bug fixed and parallelism reworked, a 1.0 release is the most plausible next step.

S
spatstat
ANALYTICS
0.0

The spatstat umbrella package, now mostly a pointer to the sub-packages doing the work

◆ Current state

spatstat is the front package of a family that was split into specialised components — spatstat.geom, spatstat.random, spatstat.model, spatstat.explore, spatstat.univar and spatstat.sparse. Its own release notes reflect that: entries in this window are largely announcements of where the real changes landed, plus documentation and cross-reference maintenance. The codebase it fronts passed 200,000 lines as of 3.5-1.

◆ Where it's heading

The split is effectively complete and the umbrella's role has settled into coordination — tracking version dependencies across sub-packages and pointing users to them. The family has kept subdividing over this period, with spatstat.univar joining in 3.1-0. The one substantive user-facing addition here is documentation infrastructure: 3.3-0 added the ability to list the history of changes to a specific function, which is a navigational answer to a codebase now spread across many packages.

◆ Prediction

Expect this package's notes to continue summarising sub-package activity rather than carrying features of its own, since every release in this window does exactly that. Read spatstat.geom, spatstat.random and spatstat.model for the substance.

Alternatives to kernelshap and spatstat

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 kernelshap or spatstat.

See all kernelshap alternatives → · See all spatstat alternatives →

Recent activity from kernelshap and spatstat

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

  1. 2mo agospatstatSub-package updates across sparse, univar and random
  2. 6mo agospatstatspatstat passes 200,000 lines of code
  3. 10mo agospatstatNew vignette documenting NA spatial objects
  4. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  5. 1y agokernelshapSampling permutation SHAP with standard errors
  6. 1y agospatstatPer-function change history now listable
  7. 1y agokernelshapBackground data now optional; ranger survival support
  8. 2y agokernelshapFactor-valued predictions dropped
  9. 2y agospatstatspatstat.univar joins the package family
  10. 2y agokernelshapadditive_shap() explains additive models exactly
  11. 2y agokernelshapFaster on plain data.frames
  12. 3y agospatstatSub-package cross-references and docs corrected

Frequently asked questions

What is the difference between kernelshap and spatstat?

They serve adjacent needs but don't currently overlap on shipped themes. kernelshap and spatstat 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 kernelshap better than spatstat?

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

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

What are the best alternatives to spatstat?

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