mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of massProps and plssem — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | massProps | plssem |
|---|---|---|
| Sector | Infra & APIs | Infra & APIs |
| Velocity score | 0.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | systems-engineering, mass-properties, uncertainty-propagation, documentation | structural-equation-modeling, partial-least-squares, multilevel-models, standard-errors |
| Last editorial update | 1h ago | 2h ago |
| Website | Visit → | Visit → |
A mass-properties rollup spends a year on documentation and follows its sibling's API
massProps computes mass, centre of mass and inertia tensors — and their uncertainties — over tree-structured assemblies, the calculation systems engineers run on a spacecraft or vehicle breakdown. It sits on top of rollupTree, the same author's generic recursive-computation engine, and its most recent release exists only to adopt accessor functions that sibling added two weeks earlier.
plssem took PLS-SEM into multilevel data, then spent two releases making the estimates trustworthy.
plssem is a young R implementation of partial least squares structural equation modelling, three CRAN releases old and shipping monthly. Its distinguishing work is the MC-PLS family — consistent PLS estimators the maintainer extended to mixed-effects designs in June — and the releases since have been about getting standard errors, admissibility and fit measures onto the same footing as the point estimates.
massProps computes mass, centre of mass and inertia tensors — and their uncertainties — over tree-structured assemblies, the calculation systems engineers run on a spacecraft or vehicle breakdown. It sits on top of rollupTree, the same author's generic recursive-computation engine, and its most recent release exists only to adopt accessor functions that sibling added two weeks earlier.
Every release in the window is documentation, benchmarks, or keeping in step with rollupTree. The inertia tensor and radius-of-gyration uncertainty equations have been reformatted and re-explained three separate times, which suggests the hard part of this package is not the computation but making the covariance treatment legible to the engineers meant to trust it. Development effort clearly sits in the engine underneath, not here.
The pattern is unambiguous: rollupTree ships an API change and massProps follows within a fortnight. Whatever the engine does next is what appears here next, and on this evidence it will arrive as a one-line release note.
plssem is a young R implementation of partial least squares structural equation modelling, three CRAN releases old and shipping monthly. Its distinguishing work is the MC-PLS family — consistent PLS estimators the maintainer extended to mixed-effects designs in June — and the releases since have been about getting standard errors, admissibility and fit measures onto the same footing as the point estimates.
The pattern is capability first, inference second. Multilevel MC-PLSc and MC-OrdPLSc arrived in 0.1.2 together with Monte-Carlo delta-method standard errors and a Polyak-Juditsky extrapolation step; 0.1.3 then extended delta-method errors to redundant parameters and thresholds, optimized their computation, added a loglikelihood-based fit measure and generated dynamic bounds to keep MC-PLS solutions admissible. Admissibility recurs throughout — penalized inadmissible solutions in 0.1.1, variance lower bounds and negative residual variance handling in 0.1.3, and an option to drop inadmissible bootstraps rather than silently include them. The release notes are pull-request lists, so the reasoning behind each change stays in the repository.
The MIMIC mode and GLS estimator both landed in the most recent release without the standard-error and fit-measure work that followed earlier additions, so extending inference to cover them is the natural next step. Bootstrap defaults moving to 500 replications suggests runtime is a live constraint and further optimization is likely.
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 massProps or plssem.
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 massProps alternatives → · See all plssem alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. massProps and plssem 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. massProps and plssem 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 massProps alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "massProps alternatives" section above for the current picks, or visit /alternatives/massprops for the full list with editorial commentary on each.
Top plssem alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "plssem alternatives" section above for the current picks, or visit /alternatives/plssem for the full list with editorial commentary on each.