simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of incase and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.
A safer case_when that keeps hardening its guarantees while realigning to tidyverse naming.
incase supplies in_case(), switch_case(), grep_case() and fn_case() as vectorised recoding functions in the dplyr::case_when idiom, with _fct and _list variants that return factors or lists instead of forcing atomic type conversion. The 0.4.0 release deprecates the undotted preserve, default and ordered arguments in favour of dotted forms, starting a removal clock, and adds .exhaustive to error on unmatched inputs.
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.
incase supplies in_case(), switch_case(), grep_case() and fn_case() as vectorised recoding functions in the dplyr::case_when idiom, with _fct and _list variants that return factors or lists instead of forcing atomic type conversion. The 0.4.0 release deprecates the undotted preserve, default and ordered arguments in favour of dotted forms, starting a removal clock, and adds .exhaustive to error on unmatched inputs.
The arc is consistently toward catching recoding mistakes at the call site rather than letting them pass silently. Early releases broadened how a match can be expressed — pattern matching, function application, factor and list returns. Recent work has shifted to guarantees about the result: correct factor level ordering relative to .default, and now an exhaustiveness check. Notably 0.4.0 reverses the 0.3.2 decision to accept arguments with or without dots, trading that flexibility for namespace safety against user-supplied case names.
The deprecation warnings introduced in 0.4.0 point to a follow-up release that removes the undotted arguments outright. Whether .exhaustive eventually becomes the default is unclear from these entries.
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 incase 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 incase alternatives → · See all kde1d alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. incase 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. incase 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 incase alternatives in Analytics are ranked by recent ship velocity. Browse the "incase alternatives" section above for the current picks, or visit /alternatives/incase 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.