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delaporte vs distributions3

A side-by-side editorial comparison of delaporte and distributions3 — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:probability-distributionsr-package

delaporte vs distributions3: at a glance

Featuredelaportedistributions3
SectorAnalyticsAnalytics
Velocity score0.06.3
Sparks · 30d01
Top themesprobability-distributions, count-data, fortran, openmpr-package, probability-distributions, empirical-distributions, likelihood-inference
Last editorial update2d ago8h 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 distributions3?

distributions3 0.3.0 adds sample-based distributions and likelihood derivatives

An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.

Read the full distributions3 trajectory →

delaporte vs distributions3: 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.

D6.3

distributions3 0.3.0 adds sample-based distributions and likelihood derivatives

◆ Current state

An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.

◆ Where it's heading

Growth used to arrive as new distribution families contributed from outside - the extreme-value set, Erlang, later the Poisson binomial. This release changes the axis: alongside two new distributions it adds an inference layer (score, hessian) and a forecast-evaluation one (crps() methods against scoringRules), which are capabilities about distributions rather than more of them. Dependency weight is being cut at the same time, with ggplot2 demoted to Suggests and glue replaced by base R sprintf().

◆ Prediction

With numeric fallbacks and the derivative generics in place, expect analytic score() and hessian() methods to be filled in across more of the distribution catalogue. The constructor-default change is the likeliest source of follow-up fixes, since calls like Poisson() now return a length-zero distribution where they previously errored.

Alternatives to delaporte and distributions3

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 distributions3.

See all delaporte alternatives → · See all distributions3 alternatives →

Recent activity from delaporte and distributions3

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

  1. 9h agodistributions3Empirical distributions, plus score and hessian generics
  2. 29d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
  3. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  4. 1y agodelaporteThread limit moves to an environment variable; Fortran type checks tightened
  5. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  6. 3y agodelaporteExplicit OpenMP thread control functions added
  7. 3y agodelaporteCRAN release 8.1.1
  8. 3y agodelaporteCRAN release 8.1.0
  9. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  10. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic

Frequently asked questions

What is the difference between delaporte and distributions3?

Both compete on the same themes — probability-distributions, r-package — within Analytics. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is delaporte better than distributions3?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. 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 distributions3?

Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.