monitOS
monitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
A side-by-side editorial comparison of kernelshap and spatstat.geom — release velocity, themes, recent moves, and the top alternatives to consider.
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.
The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics
spatstat.geom holds the spatial data structures and geometric operations the rest of the spatstat family builds on — windows, tessellations, images, point patterns and the operations that move between them. Recent releases split their attention between extending those structures to three dimensions and hardening the discretisation code where polygonal geometry meets a pixel grid. 3.8-2 adds more capabilities for three-dimensional point patterns.
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.
spatstat.geom holds the spatial data structures and geometric operations the rest of the spatstat family builds on — windows, tessellations, images, point patterns and the operations that move between them. Recent releases split their attention between extending those structures to three dimensions and hardening the discretisation code where polygonal geometry meets a pixel grid. 3.8-2 adds more capabilities for three-dimensional point patterns.
Two threads run through this window. The first is a family-wide push into 3D that originated in the simulation package and has now reached the geometry layer. The second is a slower semantic change: 3.5-0 introduced missing or unavailable (NA) spatial objects, and 3.6-0 followed with more facilities for handling them, meaning an absent window or image became a representable value rather than an error. Around both, the plotting and discretisation code accretes steadily — nonlinear colour maps, plot backgrounds, transparency control, signed distance transforms, and repeated attention to boundary pixels.
Expect the 3D surface here to keep filling in behind the simulation package rather than leading it, given that 3.8-2 follows the 3D simulation release by two months. The entries give no indication that the NA work is finished, since it has already spanned two releases.
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.geom.
monitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
filtro moves to S7 and multiplies its feature-scoring methods in a single release.
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.
See all kernelshap alternatives → · See all spatstat.geom alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. spatstat.geom is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. spatstat.geom is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
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.
Top spatstat.geom alternatives in Analytics are ranked by recent ship velocity. Browse the "spatstat.geom alternatives" section above for the current picks, or visit /alternatives/spatstat-geom for the full list with editorial commentary on each.