simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of kde1d and nat.nblast — 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.
The NBLAST neuron-similarity engine is stable code on life support, shipping once every few years.
nat.nblast implements NBLAST, the pairwise neuron-morphology similarity algorithm used across the natverse for matching and clustering traced neurons — nblast(), nhclust() and the scoring-matrix machinery around them. The algorithm and its interface have not changed in a decade of releases; recent work is CRAN compliance and build infrastructure.
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.
nat.nblast implements NBLAST, the pairwise neuron-morphology similarity algorithm used across the natverse for matching and clustering traced neurons — nblast(), nhclust() and the scoring-matrix machinery around them. The algorithm and its interface have not changed in a decade of releases; recent work is CRAN compliance and build infrastructure.
The four-year gap between 1.6.6 and 1.6.8 says most of it: this is finished code being kept on CRAN rather than a package under development. The 1.6.8 release fixes Rd cross-references and moves continuous integration to GitHub Actions, with no user-facing change at all. The last release that altered numerical output was 1.6.6 in 2021.
Expect further releases only when CRAN check policy or a natverse dependency forces one. Nothing in these entries suggests algorithmic work is underway.
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 nat.nblast.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all kde1d alternatives → · See all nat.nblast alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. kde1d and nat.nblast 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 nat.nblast 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 nat.nblast alternatives in Analytics are ranked by recent ship velocity. Browse the "nat.nblast alternatives" section above for the current picks, or visit /alternatives/nat-nblast for the full list with editorial commentary on each.