jSDM
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
A side-by-side editorial comparison of aftables and mice — release velocity, themes, recent moves, and the top alternatives to consider.
Accessible government spreadsheets in R, rebuilt on openxlsx2 and renamed along the way.
aftables generates spreadsheets that meet the UK Analysis Function's accessibility guidance, taking structured input and producing a formatted workbook with cover, contents, notes and table sheets. Version 2.0.0 replaced the workbook engine with openxlsx2 and added configuration through a config.yaml file, with create_config_yaml() exporting a template and generate_workbook() gaining arguments to point at it. The package was previously called a11ytables and was renamed in 1.0.2, with function names changed to match.
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.
aftables generates spreadsheets that meet the UK Analysis Function's accessibility guidance, taking structured input and producing a formatted workbook with cover, contents, notes and table sheets. Version 2.0.0 replaced the workbook engine with openxlsx2 and added configuration through a config.yaml file, with create_config_yaml() exporting a template and generate_workbook() gaining arguments to point at it. The package was previously called a11ytables and was renamed in 1.0.2, with function names changed to match.
The history reads in two phases. As a11ytables the work was about what belongs in an accessible spreadsheet, adding arbitrary pre-table metadata rows and enforcing rules such as rejecting tab titles that start with a numeral. Since the rename the work has been structural: a new backend, and configuration moved out of function arguments into a file that can be version-controlled and shared across a team. That second phase suits the audience, since government analysts producing recurring statistical releases want the same document properties applied every time rather than re-specified per run.
Expect the config.yaml surface to grow to cover more of what is currently passed as arguments, given it arrived alongside alternative author, title and keywords arguments that it plainly supersedes. With the openxlsx2 migration complete, further releases are likely to be formatting fixes surfaced by real departmental publications, as 2.0.1 already was.
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 aftables or mice.
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.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
State-panel tooling holding steady since its 2020 data and ergonomics release.
Five years of compiler and CRAN fixes on a capture-recapture package.
See all aftables alternatives → · See all mice alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. aftables 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. aftables 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 aftables alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "aftables alternatives" section above for the current picks, or visit /alternatives/aftables 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.