mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of midr and packageRank — 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.
CRAN download analytics maintained one micro-change at a time, hundreds per year
packageRank computes download counts and percentile ranks from CRAN's logs, with a filtering layer that tries to separate real installs from mirrors, sequences and bots. The recent releases are dense lists of small changes — thirty or more per version — spread across plot arguments, filter behaviour, and the cranDistribution object that now absorbs what packageDistribution() used to do separately.
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.
packageRank computes download counts and percentile ranks from CRAN's logs, with a filtering layer that tries to separate real installs from mirrors, sequences and bots. The recent releases are dense lists of small changes — thirty or more per version — spread across plot arguments, filter behaviour, and the cranDistribution object that now absorbs what packageDistribution() used to do separately.
There is no directional arc here; there is a maintainer keeping a measurement instrument calibrated against a data source that keeps moving. CRAN's logs went missing for a week in 2025 and the package now ships those dates as data and draws them as polygons on every plot. A chatgpt argument has been threaded through the plotting functions since 0.9.6. Function surface churns constantly — arguments renamed, plot helpers archived, others integrated.
Given the cadence, the next release will be another few dozen adjustments concentrated wherever CRAN's logs last surprised the maintainer. The consolidation of plotting arguments toward a single axis.package annotation looks unfinished.
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 packageRank.
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 packageRank 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 packageRank 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 packageRank 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 packageRank alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "packageRank alternatives" section above for the current picks, or visit /alternatives/packagerank for the full list with editorial commentary on each.