mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of ncmR and samplr — release velocity, themes, recent moves, and the top alternatives to consider.
Three weeks from first CRAN submission to a point-and-click neutral community model
ncmR fits the neutral community model to microbiome and ecological abundance data. The whole feed is three weeks long: fit_ncm() and summary methods at 0.1.0 on 1 April, a scatter plot with fitted curve and confidence interval at 0.2.0, then a Shiny application wrapping both at 0.3.0, then a row-name bugfix. It is a new package moving fast in its first month.
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.
ncmR fits the neutral community model to microbiome and ecological abundance data. The whole feed is three weeks long: fit_ncm() and summary methods at 0.1.0 on 1 April, a scatter plot with fitted curve and confidence interval at 0.2.0, then a Shiny application wrapping both at 0.3.0, then a row-name bugfix. It is a new package moving fast in its first month.
The direction is toward users who do not write R. Version 0.2.0 added plotting, 0.3.0 wrapped fitting and plotting in Shiny modules, and the same release deleted the Unicode plotting helpers introduced one version earlier because the dependency they existed for was removed. That willingness to throw away a week-old API suggests the surface is still being negotiated rather than settled.
With a fitting module and a plotting module in the app, the remaining gap is getting results back out — export of fitted parameters or figures from the Shiny session. The bugfix at 0.3.1 was in file upload, which is where a GUI's problems usually start.
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 ncmR 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.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ncmR 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. ncmR 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 ncmR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ncmR alternatives" section above for the current picks, or visit /alternatives/ncmr 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.