usmap
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
A side-by-side editorial comparison of mice and packageRank — release velocity, themes, recent moves, and the top alternatives to consider.
mice can finally predict, not just estimate, from multiply imputed data.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
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.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.
predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.
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 mice or packageRank.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
State-panel tooling holding steady since its 2020 data and ergonomics release.
Five years of compiler and CRAN fixes on a capture-recapture package.
A first release that turns meta-analytic heterogeneity into interpretable subgroups.
A meta-analysis toolkit still renaming its own API as it adds effect sizes.
See all mice 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. mice 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. mice 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 mice alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mice alternatives" section above for the current picks, or visit /alternatives/mice 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.