simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of delaporte and effectplots — release velocity, themes, recent moves, and the top alternatives to consider.
A Fortran-backed Delaporte distribution package where every release is compiler and CRAN weather.
Delaporte supplies the density, distribution, quantile and random-generation functions for the Delaporte distribution — a Poisson-negative-binomial convolution used for overdispersed count data — implemented in Fortran and called through C. The only user-facing addition in the visible history is explicit OpenMP thread control via getDelapThreads() and setDelapThreads() at 8.2.0.
A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
Delaporte supplies the density, distribution, quantile and random-generation functions for the Delaporte distribution — a Poisson-negative-binomial convolution used for overdispersed count data — implemented in Fortran and called through C. The only user-facing addition in the visible history is explicit OpenMP thread control via getDelapThreads() and setDelapThreads() at 8.2.0.
The maintenance burden here is portability, not statistics. Recent entries track a Fortran suffix change for Intel compiler compatibility, architecture-specific test tolerances, type-safety corrections on values crossing the C-to-Fortran boundary, and a thread-count variable relocated from R options to an environment variable to follow an upstream R commit. The distribution functions themselves are settled; what changes is how the compiled code is built and checked across CRAN's platform matrix.
Expect the next release to follow another CRAN toolchain or Writing R Extensions policy change, as the last several have. Two of the four visible entries carry no notes at all, so this feed will keep understating what actually shipped.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
After 0.2.0 the work turns to the awkward cases - missing values on the x axis, explicit and empty factor levels, discrete grid detection. The package is also widening past a single modelling ecosystem: h2o support and tidymodels examples arrived with 0.2.0, and fcut() was exported as a fast replacement for cut(). Release notes are issue-numbered throughout, so the roadmap is effectively the issue tracker.
Expect continued default tuning around collapse_m and discrete_m plus more model-backend coverage; the cadence points to another batch of issue fixes rather than a new plot type.
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 delaporte or effectplots.
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 delaporte alternatives → · See all effectplots alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. delaporte and effectplots 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. delaporte and effectplots 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 delaporte alternatives in Analytics are ranked by recent ship velocity. Browse the "delaporte alternatives" section above for the current picks, or visit /alternatives/delaporte for the full list with editorial commentary on each.
Top effectplots alternatives in Analytics are ranked by recent ship velocity. Browse the "effectplots alternatives" section above for the current picks, or visit /alternatives/effectplots for the full list with editorial commentary on each.