TrendLSW
Wavelet trend estimation tightens the defaults it shipped with.
A side-by-side editorial comparison of emuR and midr — release velocity, themes, recent moves, and the top alternatives to consider.
The R half of the EMU speech database system, fixing what was quietly broken.
emuR is the R interface to the EMU Speech Database Management System — loading annotated speech corpora, running hierarchical queries over annotation levels, extracting signal track data, and serving corpora to the EMU-webApp for browser-based annotation. It is at 2.6.0 on a slow cadence of roughly one release a year. Recent work has centred on the CRUD operations for annotation items and on widening what serve() can hand the web application.
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.
emuR is the R interface to the EMU Speech Database Management System — loading annotated speech corpora, running hierarchical queries over annotation levels, extracting signal track data, and serving corpora to the EMU-webApp for browser-based annotation. It is at 2.6.0 on a slow cadence of roughly one release a year. Recent work has centred on the CRUD operations for annotation items and on widening what serve() can hand the web application.
The releases read as a package being brought up to the standard its own API implied. delete_itemsInLevel() shipped in 2.1.1 as a first version, was described in 2.5.0 as heavily flawed and now usable, and the create/update/delete family is still called ongoing work. Alongside that, the query engine was rewritten onto CTEs and the signal-processing layer is being opened past the bundled wrassp, starting with Matlab. Speed work recurs — SQLite transactions, prepared statements, on-the-fly caching — consistent with corpora outgrowing the original design.
Two threads are explicitly unfinished: the CRUD documentation and behaviour, described as ongoing, and the add_signalVia family, described as a draft starting with Matlab. Expect the next release to advance one of them rather than open new ground.
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 emuR or midr.
Wavelet trend estimation tightens the defaults it shipped with.
Back from CRAN removal under a new maintainer, with the compiled layer rebuilt.
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.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. emuR 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. emuR 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 emuR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "emuR alternatives" section above for the current picks, or visit /alternatives/emur 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.