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distributions3 vs n2kanalysis

A side-by-side editorial comparison of distributions3 and n2kanalysis — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

distributions3 vs n2kanalysis: at a glance

Featuredistributions3n2kanalysis
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesr-package, probability-distributions, statistical-modelling, maintainershipbiodiversity-monitoring, inla, bayesian-models, s3-storage
Last editorial update48m ago1h ago
WebsiteVisit →Visit →

What is distributions3?

distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.

An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.

Read the full distributions3 trajectory →

What is n2kanalysis?

n2kanalysis has spent eight years wiring INLA models to an S3 bucket.

n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.

Read the full n2kanalysis trajectory →

distributions3 vs n2kanalysis: editorial side-by-side

D2.5

distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.

◆ Current state

An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.

◆ Where it's heading

The package's growth has come in two modes. Early releases absorbed whole families of distributions from outside contributors — the extreme-value set, Erlang, later the Poisson binomial — while later ones tightened the interface itself with is_discrete() and is_continuous() generics and elementwise type-safety when applying a distribution vector to a numeric vector. The handover is the notable event in the current window: maintenance moves to the author of the surrounding statistical ecosystem this package already integrates with through prodist() and countreg, which suggests the interface work will continue over the distribution-collection work.

◆ Prediction

Expect closer alignment with Zeileis's own packages, with prodist() coverage widening to more model classes; the entries here do not indicate whether new distribution families remain on the agenda.

N
n2kanalysis
ANALYTICS
0.0

n2kanalysis has spent eight years wiring INLA models to an S3 bucket.

◆ Current state

n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.

◆ Where it's heading

Development is slow, institutional, and driven by the modeling needs of specific monitoring programmes rather than a product roadmap. The pattern across the window is a new model class when the ecology requires one, then a stretch of infrastructure work around storage, credentials and pipeline efficiency. The 0.4.1 release is characteristic — a credentials helper, better result retrieval, more tests and a code-style pass, with no modeling change at all. Much of the early history is recorded only as merge-commit titles, so the release record thins out the further back it goes.

◆ Prediction

Expect the next substantive release to add another INLA model variant as a monitoring programme needs it, with S3 and credential handling continuing to absorb the maintenance effort in between.

Alternatives to distributions3 and n2kanalysis

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 distributions3 or n2kanalysis.

See all distributions3 alternatives → · See all n2kanalysis alternatives →

Recent activity from distributions3 and n2kanalysis

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

  1. 24d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
  2. 4mo agon2kanalysisconnect_inbo_s3() exposes temporary credentials to R
  3. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  4. 1y agon2kanalysisINLA models with SPDE elements supported
  5. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  6. 2y agon2kanalysisfit_model() made more efficient
  7. 3y agon2kanalysisHurdle models with imputation added
  8. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  9. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic
  10. 7y agon2kanalysisImputed data handling improvements
  11. 7y agon2kanalysisINLA models consolidated onto a single class

Frequently asked questions

What is the difference between distributions3 and n2kanalysis?

Both compete on the same themes — r-package — within Analytics. distributions3 is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 distributions3 better than n2kanalysis?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 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.

What are the best alternatives to n2kanalysis?

Top n2kanalysis alternatives in Analytics are ranked by recent ship velocity. Browse the "n2kanalysis alternatives" section above for the current picks, or visit /alternatives/n2kanalysis for the full list with editorial commentary on each.