simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of forrel and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.
forrel is getting faster at the simulations forensic kinship work actually spends its time on.
forrel handles forensic pedigree analysis: kinship likelihood ratios, profile simulation, relationship checking, and missing person calculations. Version 1.9.0 synced with pedtools 2.11.0's loop handling, which the release notes credit with enabling complex pedigrees that were previously intractable, and moved profileSim() to mirai for parallelism. It also added fEstimate() for inbreeding coefficients and parentChildLikelihood() as a fast path for the simplest case.
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.
forrel handles forensic pedigree analysis: kinship likelihood ratios, profile simulation, relationship checking, and missing person calculations. Version 1.9.0 synced with pedtools 2.11.0's loop handling, which the release notes credit with enabling complex pedigrees that were previously intractable, and moved profileSim() to mirai for parallelism. It also added fEstimate() for inbreeding coefficients and parentChildLikelihood() as a fast path for the simplest case.
Two long threads run through the window. One is making the common operations cheap: faster simulations through reorganized likelihood calculations, a dedicated parent-child path, dropped map attribute preservation, log-likelihoods to avoid underflow in kinshipLR(). The other is making relationship checking presentable, with checkPairwise() growing ggplot2 and plotly output, verbal relationship descriptions, and bootstrap p-values. Reference data is maintained alongside both, with the FORCE SNP panel completed and an X-chromosomal counterpart added.
With profileSim() on mirai and the loop handling synced, the next likely step is extending mirai parallelism to the other simulation-heavy functions such as exclusionPower() and the bootstrap in checkPairwise().
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.
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 forrel or kde1d.
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 forrel alternatives → · See all kde1d alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. forrel and kde1d 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. forrel and kde1d 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 forrel alternatives in Analytics are ranked by recent ship velocity. Browse the "forrel alternatives" section above for the current picks, or visit /alternatives/forrel for the full list with editorial commentary on each.
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.