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delaporte vs svines

A side-by-side editorial comparison of delaporte and svines — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

delaporte vs svines: at a glance

Featuredelaportesvines
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesprobability-distributions, count-data, fortran, openmpvine-copulas, time-series, dependence-modelling, rcpp
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is delaporte?

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.

Read the full delaporte trajectory →

What is svines?

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.

Read the full svines trajectory →

delaporte vs svines: editorial side-by-side

D
delaporte
ANALYTICS
0.0

A Fortran-backed Delaporte distribution package where every release is compiler and CRAN weather.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

S
svines
ANALYTICS
0.0

Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to delaporte and svines

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 svines.

See all delaporte alternatives → · See all svines alternatives →

Recent activity from delaporte and svines

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1y agodelaporteThread limit moves to an environment variable; Fortran type checks tightened
  2. 1y agosvinessvines 0.2.7
  3. 1y agosvinesAdapted to new rvinecopulib version
  4. 2y agosvinesPseudo residuals and logLik support added
  5. 3y agodelaporteExplicit OpenMP thread control functions added
  6. 3y agodelaporteCRAN release 8.1.1
  7. 3y agodelaporteCRAN release 8.1.0

Frequently asked questions

What is the difference between delaporte and svines?

Both compete on the same themes — r-package — within Analytics. delaporte 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.

Is delaporte better than svines?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. delaporte 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.

What are the best alternatives to delaporte?

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.

What are the best alternatives to svines?

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.