mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of Rmonize and samplr — release velocity, themes, recent moves, and the top alternatives to consider.
Collapsed a pile of parameters into one object and renamed every report column
Rmonize supports data harmonization: taking heterogeneous input datasets, applying processing rules against a DataSchema, and producing a harmonized dossier with assessment, summary and visual reports. Version 2.0.0 reshaped how that is driven — the evaluate, summarize and visualize functions now take the dossier alone rather than six or seven parallel arguments — and renamed every column in the assessment and summary outputs into plain language. The package is closely coupled to madshapR, whose changes the notes warn may require updates to existing user code.
A cognitive-science sampling package ships once, then goes quiet for eighteen months
samplr compares human performance against sampling algorithms, giving cognitive scientists the MCMC machinery to test whether people behave like samplers. Its entire public history is three releases: a 1.0.0 in August 2024, a floating-point fix eighteen seconds later, and then nothing until a February 2026 patch. The release notes are unusually thin even by CRAN standards.
Rmonize supports data harmonization: taking heterogeneous input datasets, applying processing rules against a DataSchema, and producing a harmonized dossier with assessment, summary and visual reports. Version 2.0.0 reshaped how that is driven — the evaluate, summarize and visualize functions now take the dossier alone rather than six or seven parallel arguments — and renamed every column in the assessment and summary outputs into plain language. The package is closely coupled to madshapR, whose changes the notes warn may require updates to existing user code.
The arc runs from correctness toward interface. Version 1.0.1 was bug fixes found on real data, 1.1.0 added a debug parameter so harmonization could be tested with incomplete inputs, and 2.0.0 is a deliberate simplification that breaks existing code in exchange for a smaller surface. Renaming outputs from expressions like 'Categories::missing' and 'Nb. non-valid values' to 'Non-valid categories' and 'Number of non-valid values' points at reports being read by people who are not the person who wrote the harmonization rules.
Expect the superseded parameters and the renamed demo object to be removed outright rather than left superseded, and continued work on the visual reports, which carry the largest volume of referenced issues across all three versions.
samplr compares human performance against sampling algorithms, giving cognitive scientists the MCMC machinery to test whether people behave like samplers. Its entire public history is three releases: a 1.0.0 in August 2024, a floating-point fix eighteen seconds later, and then nothing until a February 2026 patch. The release notes are unusually thin even by CRAN standards.
The feed shows a package that shipped and stopped. The 2024 tags were both created in one sitting and say almost nothing; the 2026 release is a row-count bug in Mean_Variance() bundled with citation metadata, a dropped dependency and http-to-https link fixes — the housekeeping profile of a package being kept alive for the paper that cites it rather than actively developed.
Adding citation information to the README is usually the move of a maintainer expecting the package to be referenced rather than extended. On this cadence the next release is more likely another CRAN-hygiene patch than new algorithms; there is not enough in these notes to say otherwise.
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 Rmonize or samplr.
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 Rmonize alternatives → · See all samplr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Rmonize and samplr 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. Rmonize and samplr 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 Rmonize alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Rmonize alternatives" section above for the current picks, or visit /alternatives/rmonize for the full list with editorial commentary on each.
Top samplr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "samplr alternatives" section above for the current picks, or visit /alternatives/samplr for the full list with editorial commentary on each.