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The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of midr and ShortForm — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Automated scale shortening with lavaan, spending its releases repairing its own search algorithms.
ShortForm automates the creation of short-form psychometric scales by searching for well-fitting subsets of items, using ant colony optimization, simulated annealing and Tabu search over lavaan models. The recent releases are corrective: 0.5.7 fixed the ant colony algorithm failing to update its best model and the simulated annealing routine mis-specifying models containing factor relationships or outcome variables, and 0.5.8 fixed Tabu search under parallel workflows and with multidimensional models. Each release note carries an explicit roadmap listing refactoring for 0.6.0 and input standardisation for 0.7.0, neither of which has shipped.
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.
ShortForm automates the creation of short-form psychometric scales by searching for well-fitting subsets of items, using ant colony optimization, simulated annealing and Tabu search over lavaan models. The recent releases are corrective: 0.5.7 fixed the ant colony algorithm failing to update its best model and the simulated annealing routine mis-specifying models containing factor relationships or outcome variables, and 0.5.8 fixed Tabu search under parallel workflows and with multidimensional models. Each release note carries an explicit roadmap listing refactoring for 0.6.0 and input standardisation for 0.7.0, neither of which has shipped.
The defects being fixed are in the search itself rather than around it. An optimizer that does not correctly retain its best candidate, and a search that mis-specifies models after the first iteration, both produce plausible-looking short forms that are not the ones the method should have found, which is a harder class of problem to notice than a crash. Alongside that the package is shedding dependencies, with ggplot2, ggrepel and tidyr dropped from the plotting methods in 0.5.8. The stated intent to refactor the major functions and standardise their arguments suggests the maintainer regards the current interface as the obstacle to further work.
The roadmap repeated across these notes points to a 0.6.0 focused on refactoring the major functions, with argument and output standardisation deferred to 0.7.0. On the evidence of this window, more unit tests and further algorithm-level fixes are likelier to arrive first than either milestone.
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 midr or ShortForm.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
Spatial thinning grows a result object, and the API breaks to make room for it
See all midr alternatives → · See all ShortForm alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. midr and ShortForm 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. midr and ShortForm 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 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.
Top ShortForm alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ShortForm alternatives" section above for the current picks, or visit /alternatives/shortform for the full list with editorial commentary on each.