PINstimation
A market-microstructure toolkit that keeps adding estimators as the papers land.
A side-by-side editorial comparison of mice and Skipper — 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.
Skipper trims a 4x memory regression out of routesrv, days after shipping h2c
Zalando's HTTP router ships patch tags almost daily, and most carry a single dependency bump or a one-line auth fix. The substance in this window is v0.27.63, which stops routesrv holding an uncompressed route tree alongside the compressed buffer: retained memory in the release's own benchmark falls from 30.7 MB to 2.0 MB, undoing most of the 4x increase zone-aware routing had introduced. Around it sit narrow auth repairs, and an eskip parser change that finally accepts negative numeric arguments in predicates and filters.
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.
Zalando's HTTP router ships patch tags almost daily, and most carry a single dependency bump or a one-line auth fix. The substance in this window is v0.27.63, which stops routesrv holding an uncompressed route tree alongside the compressed buffer: retained memory in the release's own benchmark falls from 30.7 MB to 2.0 MB, undoing most of the 4x increase zone-aware routing had introduced. Around it sit narrow auth repairs, and an eskip parser change that finally accepts negative numeric arguments in predicates and filters.
Two threads run through the recent tags. The data path keeps getting real work - leastRequests balancing, then h2c end to end in v0.27.57, now the memory cost of zone-aware routing being paid back. The auth filters, by contrast, are only being maintained: token introspection, grant auth, and now the OIDC Referer handling are fixes rather than new capability, and several are follow-ups to each other rather than independent bugs.
Zone-aware routing looks like the source of the recent memory attention, so expect further tuning around route storage and the hash computation done on every pull, which the release's second benchmark already isolates. The OIDC cookie change is the second link in an auth chain that started with the grant-auth fix, and is likely to draw another follow-up.
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 Skipper.
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.
A GENCODE annotation toolkit spent its first year getting out of CRAN's way.
See all mice alternatives → · See all Skipper alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Skipper is currently shipping more aggressively (velocity 5.0 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. Skipper is currently shipping more aggressively (velocity 5.0 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 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 Skipper alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Skipper alternatives" section above for the current picks, or visit /alternatives/skipper for the full list with editorial commentary on each.