mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of midr and netdiffuseR — release velocity, themes, recent moves, and the top alternatives to consider.
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
Network diffusion analysis returns from a seven-year gap able to track several behaviours at once
netdiffuseR analyses how behaviours spread through networks — exposure, adoption timing, thresholds, and simulation of diffusion processes. Its feed has a hole: four releases from 2024 to 2026 sit directly on top of three from 2016 and 2017, with the intervening versions absent. The current line is being maintained by a widening group of contributors and, at 1.24.0, was explicitly brought back to CRAN.
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
The releases move outward along two axes at once: what can be interpreted, and how much of it fits in memory. Version 0.5.3 rebuilt the fitting path to avoid materialising large design matrices and added a save.memory option; 0.6.0 widened the response from a vector to a matrix and added parametric link functions. Class and argument names were shortened in the same release, so the package is still willing to break itself this early.
With multiple models now held in one object and visualisation methods for them, comparison across models is the surface most likely to fill out next — the collection classes exist but the notes describe manipulation and plotting rather than any comparison metric.
netdiffuseR analyses how behaviours spread through networks — exposure, adoption timing, thresholds, and simulation of diffusion processes. Its feed has a hole: four releases from 2024 to 2026 sit directly on top of three from 2016 and 2017, with the intervening versions absent. The current line is being maintained by a widening group of contributors and, at 1.24.0, was explicitly brought back to CRAN.
The recent releases read as institutional rather than exploratory: CI fixes, CRAN-readiness passes, contributed PRs from new names, bundled teaching datasets. The one structural move is 1.23.0, named for multi-adoption, which alongside a refactor of the exposure and rdiffnet internals adds a function for splitting behaviours apart — the package handling several diffusing behaviours where its object model previously carried one.
With CRAN presence restored and a dataset for a teaching game added in the newest release, the near-term direction looks like classroom and workshop use rather than new method surface. Whether multi-adoption gets its own analysis functions, rather than a splitter, is the open question these notes do not answer.
Other Infra & APIs 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 midr or netdiffuseR.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
See all midr alternatives → · See all netdiffuseR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. midr and netdiffuseR 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. midr and netdiffuseR 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 Infra & APIs products to evaluate alongside.
Top midr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "midr alternatives" section above for the current picks, or visit /alternatives/midr for the full list with editorial commentary on each.
Top netdiffuseR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "netdiffuseR alternatives" section above for the current picks, or visit /alternatives/netdiffuser for the full list with editorial commentary on each.