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kernelshap vs OneSampleMR

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

kernelshap vs OneSampleMR: at a glance

FeaturekernelshapOneSampleMR
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessmendelian randomization, r, instrumental variables, epidemiology
Last editorial update2h 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 OneSampleMR?

OneSampleMR found that argument order in a formula was silently changing its estimates

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

Read the full OneSampleMR trajectory →

kernelshap vs OneSampleMR: 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.

O
OneSampleMR
ANALYTICS
0.0

OneSampleMR found that argument order in a formula was silently changing its estimates

◆ Current state

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

◆ Where it's heading

Two threads. The first is reach — fsw() now reads models fitted by AER::ivreg(), estimatr::iv_robust() and fixest::feols() in addition to ivreg::ivreg(), which makes conditional F statistics available without refitting in the package's own idiom. The second is hardening: clear errors when more than one exposure is given or when a variable collides with the reserved name y, and print methods that no longer fail on user-specified t0 with log or logit links. Both come largely from user reports rather than a plan.

◆ Prediction

The estimator-support work has been adding one IV-fitting package at a time on outside contributions, so further backends are the likeliest next content — the package's own estimators have been stable since first release.

Alternatives to kernelshap and OneSampleMR

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 OneSampleMR.

See all kernelshap alternatives → · See all OneSampleMR alternatives →

Recent activity from kernelshap and OneSampleMR

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

  1. 1mo agoOneSampleMROneSampleMR fixes estimates broken by covariate order in the formula
  2. 5mo agoOneSampleMROneSampleMR computes conditional F for three more IV packages
  3. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  4. 1y agokernelshapSampling permutation SHAP with standard errors
  5. 1y agoOneSampleMROneSampleMR 0.1.6
  6. 1y agokernelshapBackground data now optional; ranger survival support
  7. 2y agokernelshapFactor-valued predictions dropped
  8. 2y agoOneSampleMROneSampleMR 0.1.5
  9. 2y agoOneSampleMROneSampleMR 0.1.4
  10. 2y agokernelshapadditive_shap() explains additive models exactly
  11. 2y agokernelshapFaster on plain data.frames
  12. 3y agoOneSampleMROneSampleMR 0.1.3

Frequently asked questions

What is the difference between kernelshap and OneSampleMR?

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

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

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