mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of fio and GeoThinneR — release velocity, themes, recent moves, and the top alternatives to consider.
Input-output economics in R with a Rust core, now spanning multiple regions.
fio builds and analyses input-output models in R, using an R6 object for the model and Rust with the faer crate for the linear algebra behind technical coefficients and the Leontief inverse. Version 1.0.0 extended it from single-region tables to multi-regional models with spillover analysis, and 1.1.0 immediately corrected the naming and measures that release introduced, renaming shock-origin columns that had been labelled as destinations and replacing an interdependence index with spillover balance and export share.
Spatial thinning grows a result object, and the API breaks to make room for it
GeoThinneR removes spatially redundant occurrence records before species distribution modelling. Version 2.0.0 restructured it around a GeoThinned S3 class with print, summary, plot and trial-accessor methods, replacing the bare logical vectors earlier versions returned, and reorganised the methods into three named strategies — distance, grid and precision — with the search algorithm as a separate argument. The two releases since have added a priority system for choosing which of several tied points to drop.
fio builds and analyses input-output models in R, using an R6 object for the model and Rust with the faer crate for the linear algebra behind technical coefficients and the Leontief inverse. Version 1.0.0 extended it from single-region tables to multi-regional models with spillover analysis, and 1.1.0 immediately corrected the naming and measures that release introduced, renaming shock-origin columns that had been labelled as destinations and replacing an interdependence index with spillover balance and export share.
The package built its foundation first and its scope second. The 0.1.x releases were almost entirely about making a Rust-backed R package install reliably across platforms and toolchain versions, with the actual economics settled at 0.1.0. Once that was stable, 1.0.0 added the multi-regional layer in one release, and 1.1.0 shows the usual consequence of a large surface arriving at once: names and derived measures needing correction before they harden. Breaking changes are being taken freely while the multi-regional interface is young.
Expect further refinement of the multi-regional measures before the interface settles, given that 1.1.0 revised them within three months of their introduction. The Rust core makes larger multi-regional systems tractable, so extending coverage to more published multi-region tables is the obvious direction, though these entries name no specific dataset.
GeoThinneR removes spatially redundant occurrence records before species distribution modelling. Version 2.0.0 restructured it around a GeoThinned S3 class with print, summary, plot and trial-accessor methods, replacing the bare logical vectors earlier versions returned, and reorganised the methods into three named strategies — distance, grid and precision — with the search algorithm as a separate argument. The two releases since have added a priority system for choosing which of several tied points to drop.
The package is moving from a function that returns an answer to a tool that returns something you can interrogate. Multiple thinning trials are first-class — you can ask for the largest, fetch a specific one, summarise one — and the recent work is about making the choice among tied candidates controllable rather than random. Dependency discipline runs alongside: the R-tree method was dropped when its package was not on CRAN, and spatial coverage degrades to NA rather than failing when s2 is missing.
The priority mechanism now covers all three strategies and the last release was an overflow fix in the local kd-tree path at large sizes, so scale is where the pressure is. More work on the distance methods at large N is the likelier next step than another strategy.
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 fio or GeoThinneR.
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 fio alternatives → · See all GeoThinneR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — breaking-changes — within Infra & APIs. fio and GeoThinneR 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. fio and GeoThinneR 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 fio alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "fio alternatives" section above for the current picks, or visit /alternatives/fio for the full list with editorial commentary on each.
Top GeoThinneR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "GeoThinneR alternatives" section above for the current picks, or visit /alternatives/geothinner for the full list with editorial commentary on each.