simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of reda and svines — release velocity, themes, recent moves, and the top alternatives to consider.
A mature recurrent-event toolkit in careful maintenance, shedding weight rather than adding surface.
reda provides nonparametric mean cumulative function estimation, gamma-frailty rate regression, and event-data simulation for recurrent-event survival analysis. The core API settled at 0.5.0 when Recur() replaced Survr() and the MCF internals moved to C++. Everything since has been consolidation: small argument additions, method completions, and CRAN hygiene.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
svines fits stationary vine copula models to multivariate time series, extending the rvinecopulib engine with the serial dependence structure that makes vines usable for temporal data. The visible history is three releases carrying one real addition — pseudo-residual computation and logLik support at 0.2.2 — with the rest tracking its C++ dependency.
reda provides nonparametric mean cumulative function estimation, gamma-frailty rate regression, and event-data simulation for recurrent-event survival analysis. The core API settled at 0.5.0 when Recur() replaced Survr() and the MCF internals moved to C++. Everything since has been consolidation: small argument additions, method completions, and CRAN hygiene.
The last three releases contain no new modelling capability at all — a dependency reshuffle, a test-example correction, and a print-order fix. The package is being kept installable and correct rather than extended. Its tightest coupling is to splines2, a sibling package from the same maintainer, which supplies the derivative machinery reda depends on.
Expect continued small-cadence CRAN-compliance releases tracking ggplot2 and splines2 changes. The entries show no in-progress feature work, so a substantive release would have to arrive without warning from this feed.
svines fits stationary vine copula models to multivariate time series, extending the rvinecopulib engine with the serial dependence structure that makes vines usable for temporal data. The visible history is three releases carrying one real addition — pseudo-residual computation and logLik support at 0.2.2 — with the rest tracking its C++ dependency.
This package moves when rvinecopulib moves. The 0.2.4 release exists solely to adapt to a new rvinecopulib version, and 0.2.7 carries auto-generated GitHub release notes with no description at all. It shipped on the same day as kde1d 1.1.1, another package from the same maintainer, which is the pattern to watch: changes in the shared C++ layer surface as near-simultaneous releases across the vine family rather than as independent work.
The next release most plausibly follows another rvinecopulib update rather than adding modelling capability. Two of the three visible entries carry no substantive notes, so this feed will keep underreporting what changed.
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 reda or svines.
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.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. reda and svines 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. reda and svines 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 reda alternatives in Analytics are ranked by recent ship velocity. Browse the "reda alternatives" section above for the current picks, or visit /alternatives/reda for the full list with editorial commentary on each.
Top svines alternatives in Analytics are ranked by recent ship velocity. Browse the "svines alternatives" section above for the current picks, or visit /alternatives/svines for the full list with editorial commentary on each.