mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of aftables and midr — 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.
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
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.
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
The releases move outward along two axes at once: what can be interpreted, and how much of it fits in memory. Version 0.5.3 rebuilt the fitting path to avoid materialising large design matrices and added a save.memory option; 0.6.0 widened the response from a vector to a matrix and added parametric link functions. Class and argument names were shortened in the same release, so the package is still willing to break itself this early.
With multiple models now held in one object and visualisation methods for them, comparison across models is the surface most likely to fill out next — the collection classes exist but the notes describe manipulation and plotting rather than any comparison metric.
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 midr.
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 aftables alternatives → · See all midr 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 midr 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 midr 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 midr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "midr alternatives" section above for the current picks, or visit /alternatives/midr for the full list with editorial commentary on each.