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ROOT vs distributions3

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

ROOT vs distributions3: at a glance

FeatureROOTdistributions3
SectorAnalyticsAnalytics
Velocity score0.06.3
Sparks · 30d01
Top themeshep-analysis, rntuple, rdataframe, lts-branchesr-package, probability-distributions, empirical-distributions, likelihood-inference
Last editorial update10d ago8h ago
WebsiteVisit →Visit →

What is ROOT?

ROOT is shipping the pieces of its long-promised v7 inside the v6 release line

ROOT maintains an unusual number of parallel branches — patches for 6.26, 6.28, 6.30, 6.32, 6.36 and 6.38 all landed within weeks of each other in June 2026 — because CERN experiments pin to versions for years at a time. The 6.40 LTS released in May is where the actual work is: an opt-out from automatic object registration, experimental multithreaded histograms, a new RFile interface, an libcurl-based HTTP I/O layer with S3 support, and a rebuilt ML data loader. June's patch wave is the routine consequence, closing out the 6.26 and 6.38 series while fixing the first regressions in 6.40.

Read the full ROOT 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 →

ROOT vs distributions3: editorial side-by-side

R
ROOT
ANALYTICS
0.0

ROOT is shipping the pieces of its long-promised v7 inside the v6 release line

◆ Current state

ROOT maintains an unusual number of parallel branches — patches for 6.26, 6.28, 6.30, 6.32, 6.36 and 6.38 all landed within weeks of each other in June 2026 — because CERN experiments pin to versions for years at a time. The 6.40 LTS released in May is where the actual work is: an opt-out from automatic object registration, experimental multithreaded histograms, a new RFile interface, an libcurl-based HTTP I/O layer with S3 support, and a rebuilt ML data loader. June's patch wave is the routine consequence, closing out the 6.26 and 6.38 series while fixing the first regressions in 6.40.

◆ Where it's heading

The ROOT 7 redesign is arriving piecemeal under ROOT::Experimental rather than as a version bump: RNTuple replacing TTree, RDataFrame replacing TTree::Draw, RFile replacing TFile, and now the ability to switch off the global-directory ownership model that has defined ROOT's ergonomics for decades. The team is easing migration with documentation rather than deprecation — 6.40 ships a TTree::Draw-to-RDataFrame translation guide instead of a removal notice. Build weight is being cut in the same pass, with bundled builtin packages reduced roughly fourfold in favour of system libraries.

◆ Prediction

Expect further 6.40.x patches through the year as experiments migrate onto the LTS, concentrated in RNTuple and the new histogram paths where the code is youngest. The experimental namespace is the thing to watch: features that stabilize there are the clearest available signal of what a ROOT 7 would actually contain.

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 ROOT 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 ROOT or distributions3.

See all ROOT alternatives → · See all distributions3 alternatives →

Recent activity from ROOT 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. 2mo agoROOTROOT 6.32.24 patches the 6.32 maintenance branch
  4. 2mo agoROOTROOT 6.30.12 patches the 6.30 maintenance branch
  5. 2mo agoROOTROOT 6.28.16 patches the 6.28 maintenance branch
  6. 2mo agoROOTROOT 6.38.06 closes the 6.38 series, adds Python 3.15 support
  7. 2mo agoROOTROOT 6.40.02 fixes RNTuple model extension and SOFIE padding
  8. 2mo agoROOTROOT 6.26.20 is the final patch for the 6.26 series
  9. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  10. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  11. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  12. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic

Frequently asked questions

What is the difference between ROOT and distributions3?

They serve adjacent needs but don't currently overlap on shipped themes. 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 ROOT 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 ROOT?

Top ROOT alternatives in Analytics are ranked by recent ship velocity. Browse the "ROOT alternatives" section above for the current picks, or visit /alternatives/cern-root 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.