PINstimation
A market-microstructure toolkit that keeps adding estimators as the papers land.
A side-by-side editorial comparison of mice and Volatility — 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.
Volatility 3 caught up with Volatility 2, then started reorganising itself.
The 2.26.0 release was explicitly aimed at functional parity with the archived Volatility 2, landing around twenty plugins at once across Linux, macOS and Windows. Since then the work has shifted from filling gaps to structuring what exists: malware-specific plugins moved under a malware namespace with the old names deprecated, an arrow/parquet output renderer added, volshell given breakpoints, and per-release additions like sockscan, process_spoofing, pebmasquerade and etwpatch.
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.
The 2.26.0 release was explicitly aimed at functional parity with the archived Volatility 2, landing around twenty plugins at once across Linux, macOS and Windows. Since then the work has shifted from filling gaps to structuring what exists: malware-specific plugins moved under a malware namespace with the old names deprecated, an arrow/parquet output renderer added, volshell given breakpoints, and per-release additions like sockscan, process_spoofing, pebmasquerade and etwpatch.
Two things are happening at once. The plugin catalogue keeps growing on the Linux side in particular — tracing, kallsyms, ftrace, VMA scanning, smearing protection — reflecting where memory forensics currently has the least coverage. And the framework is being made into something other tools consume: structured output formats, a shipped Windows executable, a namespaced plugin taxonomy with a year-long deprecation window. The project is treating plugin names as an interface it owes users stability on.
Expect the malware namespace migration to complete as the deprecated names age out, and the Linux plugin surface to keep taking the bulk of new additions, with output-format work continuing to open the framework to automated pipelines.
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 Volatility.
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 Volatility 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 Volatility 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 Volatility 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 Volatility alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Volatility alternatives" section above for the current picks, or visit /alternatives/volatility for the full list with editorial commentary on each.