mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of statsExpressions and stochvol — release velocity, themes, recent moves, and the top alternatives to consider.
A statistics backend whose release history is mostly other people's weather
statsExpressions produces the tidy dataframes and plotmath expressions that ggstatsplot prints onto plots, and that position defines its changelog. Six of its ten most recent versions exist to absorb API changes in easystats, dplyr or purrr. Version 2.0.0 is the exception, cut to accompany ggstatsplot's own 1.0.0 and carrying pairwise Fisher's exact post hocs for contingency tables.
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.
statsExpressions produces the tidy dataframes and plotmath expressions that ggstatsplot prints onto plots, and that position defines its changelog. Six of its ten most recent versions exist to absorb API changes in easystats, dplyr or purrr. Version 2.0.0 is the exception, cut to accompany ggstatsplot's own 1.0.0 and carrying pairwise Fisher's exact post hocs for contingency tables.
This is a component settling into place beneath a larger package rather than a product with its own roadmap. New statistical content arrives rarely and narrowly — an exact-p toggle, one post-hoc function — while the recurring work is keeping expressions correct as the easystats stack shifts underneath. The one bug class it keeps returning to is rendering: p-values of exactly zero, decimal commas that plotmath parses as list separators.
Coupled this tightly, the next release is most likely another compatibility pass timed to an easystats or ggstatsplot version rather than new tests. Nothing in these entries signals an independent feature direction.
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.
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 statsExpressions or stochvol.
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 statsExpressions alternatives → · See all stochvol alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — maintenance — within Infra & APIs. statsExpressions and stochvol 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. statsExpressions and stochvol 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 statsExpressions alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "statsExpressions alternatives" section above for the current picks, or visit /alternatives/statsexpressions for the full list with editorial commentary on each.
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.