dscore
The D-score reference implementation rebuilt its measurement foundation on seven countries.
Comparison · Infra & APIs
sdcMicro vs stochvol
A side-by-side editorial comparison of sdcMicro and stochvol — release velocity, themes, recent moves, and the top alternatives to consider.
sdcMicro vs stochvol: at a glance
What is sdcMicro?
A 20-year anonymization toolbox now has a language model inside its refinement loop.
sdcMicro is the reference R implementation of statistical disclosure control — k-anonymity, local suppression, PRAM, microaggregation, record swapping — used by national statistical offices, with a Shiny GUI (sdcApp) as its second face. The feed shows a long GUI-maintenance era through 2018-2022 and then a gap, and the package that reappears in 5.8.2 has an AI_applyAnonymization() workflow and a query_llm() helper that the older entries know nothing about. The July release tunes that loop rather than introducing it.
What is stochvol?
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.
sdcMicro vs stochvol: editorial side-by-side
sdcMicro
0.0INFRA · APIS
A 20-year anonymization toolbox now has a language model inside its refinement loop.
◆ Current state
sdcMicro is the reference R implementation of statistical disclosure control — k-anonymity, local suppression, PRAM, microaggregation, record swapping — used by national statistical offices, with a Shiny GUI (sdcApp) as its second face. The feed shows a long GUI-maintenance era through 2018-2022 and then a gap, and the package that reappears in 5.8.2 has an AI_applyAnonymization() workflow and a query_llm() helper that the older entries know nothing about. The July release tunes that loop rather than introducing it.
◆ Where it's heading
Two threads run in parallel. The visible one is the LLM-assisted anonymization path maturing: 5.8.2 gives its refinement loop early stopping via tol and patience so it stops when the combined utility score plateaus instead of burning all max_iter rounds, and teaches query_llm() to drop the temperature parameter for reasoning models that reject it. The other is unglamorous statistical correctness — a distinct l-diversity computation fixed for NAs in key variables, with the C++ simplified and tests added. The release also ships reproducibility scripts for a SoftwareX paper, which suggests the AI path is being written up rather than quietly trialled.
◆ Prediction
The provider-compatibility fix is reactive — a parameter dropped because one model family rejected it — so expect more of the same as query_llm() meets other backends. Given tol and patience were added to stop wasted iterations, cost or runtime of the refinement loop is the live concern, and further controls on it are the likeliest next move.
stochvol
0.0INFRA · APIS
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to sdcMicro and stochvol
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 sdcMicro or stochvol.
ggfootball
A football-viz package just swapped scraping for an API and broke its own output to do it.
goat
A gene-set enrichment package that outgrew its human-only origins, then went quiet.
rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
massProps
A mass-properties rollup spends a year on documentation and follows its sibling's API
writeAlizer
Six months of releases and not one of them touched the scoring models
See all sdcMicro alternatives → · See all stochvol alternatives →
Recent activity from sdcMicro and stochvol
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agosdcMicroEarly stopping for the AI anonymization loop, plus GPT-5.x support
- 5mo agostochvolSampler crash with constant parameters fixed, plus RcppArmadillo 15
- 1y agostochvolTwo CRAN check notes cleared
- 1y agostochvolProposal variance corrected in the centered parameterisation
- 2y agostochvolCRAN stochvol 3.2.4
- 2y agostochvolRolling-window indexing and inverse gamma prior validation fixed
- 3y agostochvolCore C++ sampler routines exported for reuse
- 4y agosdcMicrorecordSwap() adds targeted record swapping
- 5y agosdcMicroTwo new information-loss measures and a run of sdcApp fixes
- 5y agosdcMicroCompatibility fixes for R 4.1 sorting and rsconnect deployment
- 8y agosdcMicroMinor release, mostly GUI work
- 8y agosdcMicrodUtility() corrected so IL1 and IL1s can be distinguished
Frequently asked questions
What is the difference between sdcMicro and stochvol?
They serve adjacent needs but don't currently overlap on shipped themes. sdcMicro 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.
Is sdcMicro better than stochvol?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. sdcMicro 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.
What are the best alternatives to sdcMicro?
Top sdcMicro alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "sdcMicro alternatives" section above for the current picks, or visit /alternatives/sdcmicro for the full list with editorial commentary on each.
What are the best alternatives to stochvol?
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.