pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of JointFPM and stochvol — release velocity, themes, recent moves, and the top alternatives to consider.
Recurrent-event modelling settles, with mean_no() promoted to stable.
JointFPM fits joint flexible parametric models for a recurrent event process alongside a competing terminal event, and predicts the mean number of events. The visible history runs from bug fixes on the earliest CRAN releases through standardization, integration options and a summary method, ending with mean_no() declared stable. Several changes arrived through outside pull requests.
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.
JointFPM fits joint flexible parametric models for a recurrent event process alongside a competing terminal event, and predicts the mean number of events. The visible history runs from bug fixes on the earliest CRAN releases through standardization, integration options and a summary method, ending with mean_no() declared stable. Several changes arrived through outside pull requests.
The arc runs from a working estimator toward a usable one: input validation and error messages first, then control over the numerical integration, then a summary method and pass-through arguments to the underlying rstpm2 fit. The latest release adds no code so much as a stability commitment to a function users were already calling.
With mean_no() stable, the next work most likely targets the prediction and standardization paths rather than the model fit itself.
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 JointFPM or stochvol.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
See all JointFPM alternatives → · See all stochvol alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. JointFPM 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. JointFPM 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 JointFPM alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "JointFPM alternatives" section above for the current picks, or visit /alternatives/jointfpm 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.