RMVMR
RMVMR is being tidied in lockstep with MVMR, the package it wraps
A side-by-side editorial comparison of gridify and kernelshap — release velocity, themes, recent moves, and the top alternatives to consider.
gridify adds table pagination, the one visible feature in a single-release window.
gridify arranges plots and tables into layouts with headers and footers in R. Only one release is visible — 0.7.5 — carrying table pagination plus repository housekeeping in the form of an issue template and badges. The changelog is a pull-request list rather than written notes, so detail is thin.
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.
gridify arranges plots and tables into layouts with headers and footers in R. Only one release is visible — 0.7.5 — carrying table pagination plus repository housekeeping in the form of an issue template and badges. The changelog is a pull-request list rather than written notes, so detail is thin.
With one entry to read, direction can only be inferred from what it contains: pagination points the package toward long tables that do not fit a single output page, which is a reporting concern rather than a plotting one. Contributions come from a small named group. There is not enough history here to say whether that reporting emphasis is a trend.
Pagination usually pulls page-level controls behind it — repeating headers, row-count control — but the single entry available does not confirm any of that is planned.
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.
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.
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.
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 gridify or kernelshap.
RMVMR is being tidied in lockstep with MVMR, the package it wraps
geoarrow tracks the GeoArrow spec and otherwise just keeps compiling
n2khab keeps retracting interpretations of habitat data it can't actually support
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
OneSampleMR found that argument order in a formula was silently changing its estimates
bpbounds found the same swapped-cell bug twice and clamped its bounds back into range
See all gridify alternatives → · See all kernelshap alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r package — within Analytics. gridify and kernelshap 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. gridify and kernelshap 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 gridify alternatives in Analytics are ranked by recent ship velocity. Browse the "gridify alternatives" section above for the current picks, or visit /alternatives/gridify for the full list with editorial commentary on each.
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.