STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of kde1d and rainette — release velocity, themes, recent moves, and the top alternatives to consider.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
An R implementation of the Reinert textual clustering method, with interactive explorers for browsing clusters. The two substantive releases are behind it: 0.2.0 renamed the core segment-size arguments, fixed segment merging that had been crossing document boundaries, and added a document browser plus per-document cluster tables; 0.3.0 reworked the double classification in rainette2() with full and parallel arguments and much faster computation. The 2026 release is a vctrs compatibility fix plus a colors argument on rainette_plot().
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.
With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.
An R implementation of the Reinert textual clustering method, with interactive explorers for browsing clusters. The two substantive releases are behind it: 0.2.0 renamed the core segment-size arguments, fixed segment merging that had been crossing document boundaries, and added a document browser plus per-document cluster tables; 0.3.0 reworked the double classification in rainette2() with full and parallel arguments and much faster computation. The 2026 release is a vctrs compatibility fix plus a colors argument on rainette_plot().
The package moved from correct-enough to trustworthy and then to maintained: results-changing fixes first, performance and options second, and now only upstream compatibility and small user-requested arguments. Wordcloud plots were flagged for deprecation in 0.3.0 and pulled from the explorers, narrowing the output surface rather than growing it. The same maintainer's questionr followed the same pattern in the same period.
The deprecated wordcloud plot type is the obvious removal candidate, since it has carried a warning since 0.3.0 and has already been dropped from the interactive explorers.
Other Analytics 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 kde1d or rainette.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all kde1d alternatives → · See all rainette alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. kde1d and rainette 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. kde1d and rainette 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 Analytics products to evaluate alongside.
Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.
Top rainette alternatives in Analytics are ranked by recent ship velocity. Browse the "rainette alternatives" section above for the current picks, or visit /alternatives/rainette for the full list with editorial commentary on each.