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kernelshap vs mrbayes

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

kernelshap vs mrbayes: at a glance

Featurekernelshapmrbayes
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessmendelian-randomization, bayesian-inference, stan, jags
Last editorial update3h ago48m 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 mrbayes?

mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.

mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.

Read the full mrbayes trajectory →

kernelshap vs mrbayes: 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.

M
mrbayes
ANALYTICS
0.0

mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.

◆ Current state

mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.

◆ Where it's heading

The package has moved from packaging upkeep into a correctness-audit phase. 0.5.3 fixes a hardcoded three-exposure loop in MVMR-Egger reporting, a broken joint-prior branch, a sigma parameterization error in radial Egger, and several prior specifications — the profile of a maintainer reading their own model files closely rather than responding to bug reports. Platform work continues underneath: an R 4.3.0 floor inherited through a transitive dependency chain, and segfault fixes on macOS ARM.

◆ Prediction

Expect further audit-driven patches to the remaining rjags and Stan model files rather than new estimators; the fixes in 0.5.3 cluster in the Egger variants, which suggests that is where the reading is still in progress.

Alternatives to kernelshap and mrbayes

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 mrbayes.

See all kernelshap alternatives → · See all mrbayes alternatives →

Recent activity from kernelshap and mrbayes

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

  1. 1mo agomrbayesEstimator audit fixes MVMR-Egger loops and radial Egger sigma
  2. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  3. 1y agokernelshapSampling permutation SHAP with standard errors
  4. 1y agomrbayesMVMR rjags example gated on rjags being installed
  5. 1y agomrbayesExamples and tests skip when rstan or rjags is missing
  6. 1y agomrbayespkgdown site updated
  7. 1y agomrbayesHelper command added for installing JAGS
  8. 1y agomrbayesDependency surface trimmed; maintainer handover
  9. 1y agokernelshapBackground data now optional; ranger survival support
  10. 2y agokernelshapFactor-valued predictions dropped
  11. 2y agokernelshapadditive_shap() explains additive models exactly
  12. 2y agokernelshapFaster on plain data.frames

Frequently asked questions

What is the difference between kernelshap and mrbayes?

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

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

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