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 washdata — 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.
washdata is a fixed survey dataset; eight years of releases have changed only its packaging.
A data package distributing the Urban Water and Sanitation Survey, on CRAN since January 2018. No release has altered the data. The 2018 pair added survey country, year and aim to DESCRIPTION and fixed a README link; everything since — 2020, 2024 and the January 2026 release — is documentation, formatting, badges, repository refreshes and updates for a new rhub version.
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.
A data package distributing the Urban Water and Sanitation Survey, on CRAN since January 2018. No release has altered the data. The 2018 pair added survey country, year and aim to DESCRIPTION and fixed a README link; everything since — 2020, 2024 and the January 2026 release — is documentation, formatting, badges, repository refreshes and updates for a new rhub version.
Nothing is heading anywhere, and for a dataset package that is the point: the value is a citable, unchanging artifact, and the release history exists to keep it installable as R's toolchain moves. The maintenance cadence matches the maintainer's other nutrition packages, which received the same repository-refresh treatment in the same period. Note also that the tags are backfilled out of order — v0.1.0 carries a later stamp than v0.1.2.
Expect further releases only when CRAN checks or infrastructure require them; there is no indication the survey data itself will be extended.
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 washdata.
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 washdata 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 washdata 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 washdata 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 washdata alternatives in Analytics are ranked by recent ship velocity. Browse the "washdata alternatives" section above for the current picks, or visit /alternatives/washdata for the full list with editorial commentary on each.