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mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of stochvol and Volatility — release velocity, themes, recent moves, and the top alternatives to consider.
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
stochvol runs MCMC for stochastic volatility models, with a C++ sampler underneath an R interface. Five years of releases in this window contain no new models: the work is compiler and dependency compatibility, CRAN check notes, and a steady trickle of corrections to the sampler itself. Its methodological milestone, the Journal of Statistical Software paper, is recorded in a 2021 tag.
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.
stochvol runs MCMC for stochastic volatility models, with a C++ sampler underneath an R interface. Five years of releases in this window contain no new models: the work is compiler and dependency compatibility, CRAN check notes, and a steady trickle of corrections to the sampler itself. Its methodological milestone, the Journal of Statistical Software paper, is recorded in a 2021 tag.
This is what a finished computational package looks like. The formula interface arrived at 3.1.0 and nothing has been added since; what changes is the ground underneath — RcppArmadillo major versions, UBSan checks, error-handling conventions moving from Rf_error to Rcpp::stop for correct memory management. The recurring pattern worth watching is that several releases fix real errors in the sampler's proposal distributions, found by users and by CRAN's own instrumented checks rather than by the maintainer.
Nothing in these notes suggests new methodology. Expect the next release when RcppArmadillo or a CRAN check flavour forces one, and treat any bug report against the samplers as the more consequential event.
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 stochvol or Volatility.
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 stochvol 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. stochvol 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. stochvol 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 stochvol alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "stochvol alternatives" section above for the current picks, or visit /alternatives/stochvol 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.