pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of jSDM and mice — release velocity, themes, recent moves, and the top alternatives to consider.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
jSDM fits joint species distribution models by Gibbs sampling, with the sampler written in C++ against GSL and Armadillo and exposed through binomial probit, binomial logit, Poisson log and Gaussian entry points. The 0.2 line extended it with species traits, constrained factor loadings and residual-association plots. The one entry since 2023 carries only a compare link.
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.
jSDM fits joint species distribution models by Gibbs sampling, with the sampler written in C++ against GSL and Armadillo and exposed through binomial probit, binomial logit, Poisson log and Gaussian entry points. The 0.2 line extended it with species traits, constrained factor loadings and residual-association plots. The one entry since 2023 carries only a compare link.
The package built out its model family quickly and then stopped: five of the six visible entries are stamped the same day as a backfilled archive, and the only later release says nothing about its contents. The direction the 0.2 line was heading, toward trait-mediated species effects and better convergence on latent variable models, has no visible continuation.
The feed does not support a confident prediction; the latest entry publishes no notes, so whether the package is still developing or only being kept CRAN-clean cannot be read from it.
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.
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 jSDM or mice.
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.
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.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. jSDM and mice 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. jSDM and mice 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 jSDM alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "jSDM alternatives" section above for the current picks, or visit /alternatives/jsdm for the full list with editorial commentary on each.
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.