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mlr3proba vs posterior

A side-by-side editorial comparison of mlr3proba and posterior — release velocity, themes, recent moves, and the top alternatives to consider.

mlr3proba vs posterior: at a glance

Featuremlr3probaposterior
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmlr3, survival-analysis, probabilistic-learning, dependency-maintenancebayesian, rvar, pareto-diagnostics, r-infrastructure
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mlr3proba?

mlr3proba is shedding weight as its survival work moves into sibling packages

mlr3proba provides probabilistic supervised learning for mlr3 — survival analysis, density estimation, and the measures that go with them. Recent releases are almost entirely upkeep: a distr6 fork to work around an upstream problem, an ooplah fix, a predict-type correction, and registration in mlr_reflections$loaded_packages. The one deletion is telling, with LearnerDensPenalized removed after pendensity left CRAN.

Read the full mlr3proba trajectory →

What is posterior?

posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.

The releases in this window advance on two fronts. The rvar random-variable type gained factor and ordered subtypes (1.4.0), rvar-indexed slicing and `rvar_ifelse()` (1.5.0), base `%*%` matrix multiplication and indexed variable names (1.6.0). Separately, Pareto diagnostics have grown from `pareto_smooth()` options and individual `pareto_khat()`-family functions (1.6.0) through `pit()` for draws and rvars (1.6.1) to exported generalized-Pareto functions and `pareto_pit` (1.7.0). 1.7.1 is a paperwork release for a JOSS submission.

Read the full posterior trajectory →

mlr3proba vs posterior: editorial side-by-side

M
mlr3proba
ANALYTICS
0.0

mlr3proba is shedding weight as its survival work moves into sibling packages

◆ Current state

mlr3proba provides probabilistic supervised learning for mlr3 — survival analysis, density estimation, and the measures that go with them. Recent releases are almost entirely upkeep: a distr6 fork to work around an upstream problem, an ooplah fix, a predict-type correction, and registration in mlr_reflections$loaded_packages. The one deletion is telling, with LearnerDensPenalized removed after pendensity left CRAN.

◆ Where it's heading

The package is being pared back rather than extended. Its README now points at survdistr and mlr3cmprsk as matured alternatives for parts of what it covers, which reads as scope being handed off, while the Cox proportional-hazards autoplot arrived from mlr3viz in the other direction. Several fixes exist to route around dependencies that broke or disappeared, which is the recurring cost of building on a long chain of specialized CRAN packages.

◆ Prediction

The dependency churn suggests more consolidation — further reliance on survdistr and mlr3cmprsk, and more learners retired when the package underneath them goes unmaintained.

P
posterior
ANALYTICS
0.0

posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.

◆ Current state

The releases in this window advance on two fronts. The rvar random-variable type gained factor and ordered subtypes (1.4.0), rvar-indexed slicing and `rvar_ifelse()` (1.5.0), base `%*%` matrix multiplication and indexed variable names (1.6.0). Separately, Pareto diagnostics have grown from `pareto_smooth()` options and individual `pareto_khat()`-family functions (1.6.0) through `pit()` for draws and rvars (1.6.1) to exported generalized-Pareto functions and `pareto_pit` (1.7.0). 1.7.1 is a paperwork release for a JOSS submission.

◆ Where it's heading

posterior is positioning itself as shared infrastructure rather than an end-user package: 1.7.0 explicitly exports generalized-Pareto machinery 'for use in other packages', and the JOSS paper is a citation vehicle for the same audience. The rvar work points the same way — a random-variable type other Bayesian packages can build on. Cadence is steady but unhurried, roughly one feature release a year.

◆ Prediction

More diagnostic functions are likely to be exported for downstream reuse, following the pattern 1.7.0 established with the generalized-Pareto helpers.

Alternatives to mlr3proba and posterior

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 mlr3proba or posterior.

See all mlr3proba alternatives → · See all posterior alternatives →

Recent activity from mlr3proba and posterior

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

  1. 2mo agoposteriorposterior 1.7.1 released for JOSS paper
  2. 2mo agomlr3probamlr3proba 0.8.10 registers itself in the mlr3 loaded-packages registry
  3. 3mo agoposteriorposterior 1.7.0 exports generalized-Pareto functions
  4. 4mo agomlr3probamlr3proba 0.8.9 drops LearnerDensPenalized after pendensity left CRAN
  5. 5mo agomlr3probamlr3proba 0.8.8
  6. 5mo agomlr3probamlr3proba 0.8.7
  7. 9mo agomlr3probamlr3proba 0.8.5
  8. 10mo agomlr3probamlr3proba 0.8.4 takes over the Cox proportional-hazards autoplot
  9. 10mo agoposteriorposterior 1.6.1 adds pit() for draws and rvars
  10. 1y agoposteriorposterior 1.6.0 adds Pareto diagnostics and ESS-based thinning
  11. 2y agoposteriorposterior 1.5.0 adds nested-Rhat and rvar indexing
  12. 3y agoposteriorposterior 1.4.0 adds factor and ordered rvar subtypes

Frequently asked questions

What is the difference between mlr3proba and posterior?

They serve adjacent needs but don't currently overlap on shipped themes. mlr3proba and posterior 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 mlr3proba better than posterior?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3proba and posterior 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 mlr3proba?

Top mlr3proba alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3proba alternatives" section above for the current picks, or visit /alternatives/mlr3proba for the full list with editorial commentary on each.

What are the best alternatives to posterior?

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