← Back to home
Comparison · Analytics

fairmodels vs spatstat.random

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

fairmodels vs spatstat.random: at a glance

Featurefairmodelsspatstat.random
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesfairness auditing, bias detection, dalex, r packagespatial-statistics, point-processes, simulation, r-package
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is fairmodels?

fairmodels sits dormant for three years, resurfacing only to satisfy a CRAN check.

fairmodels audits classification models for bias, built around fairness_check() and parity-loss metrics on top of DALEX explainers. The last substantive work dates from 2021; the 2025 release is a single-line change swapping ifelse for if/else in fairness_heatmap. Version 0.2.2 set the package's core design when it superseded metric differences with ratios.

Read the full fairmodels trajectory →

What is spatstat.random?

spatstat's simulation engine pushes point process generation into three dimensions

spatstat.random generates random point patterns and simulates point process models for the spatstat family. Its recent releases have moved along two lines at once: filling out three-dimensional simulation, and adding conditional simulation to the established cluster process generators. 3.5-1 is a narrow follow-up adding a random Dirichlet-Voronoi tessellation without edge effects.

Read the full spatstat.random trajectory →

fairmodels vs spatstat.random: editorial side-by-side

F
fairmodels
ANALYTICS
0.0

fairmodels sits dormant for three years, resurfacing only to satisfy a CRAN check.

◆ Current state

fairmodels audits classification models for bias, built around fairness_check() and parity-loss metrics on top of DALEX explainers. The last substantive work dates from 2021; the 2025 release is a single-line change swapping ifelse for if/else in fairness_heatmap. Version 0.2.2 set the package's core design when it superseded metric differences with ratios.

◆ Where it's heading

The release history describes a package that reached its intended shape early and has been custodial since — the gap from August 2022 to October 2025 carries no functional change at all. What movement exists is CRAN-driven: documentation compliance, example runtimes, coding-style notes. The fairness metrics themselves have not changed since the parity_loss corrections of 2020.

◆ Prediction

On this cadence the next release is most likely another CRAN-prompted one-liner rather than new fairness metrics; nothing in these entries points to active development.

S2.5

spatstat's simulation engine pushes point process generation into three dimensions

◆ Current state

spatstat.random generates random point patterns and simulates point process models for the spatstat family. Its recent releases have moved along two lines at once: filling out three-dimensional simulation, and adding conditional simulation to the established cluster process generators. 3.5-1 is a narrow follow-up adding a random Dirichlet-Voronoi tessellation without edge effects.

◆ Where it's heading

The clearest arc is dimensional. 3.5-0 carried inhomogeneous Poisson processes, non-uniform random points and Simple Sequential Inhibition into 3D in a single release, and the sibling geometry package followed two months later with more capabilities for three-dimensional point patterns. Alongside that, the generators have been gaining theoretical range — Gaussian random fields in 3.4-4, a new class of theoretical cluster process models and random diffusion in 3.5-0 — while earlier releases concentrated on conditional simulation and efficiency in the existing 2D routines.

◆ Prediction

Expect the 3D work to continue propagating into the model-fitting and geometry packages before spatstat.random adds another dimension-independent generator, since the 3D features here have already begun appearing downstream. The entries do not indicate which estimator gets 3D support next.

Alternatives to fairmodels and spatstat.random

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 fairmodels or spatstat.random.

See all fairmodels alternatives → · See all spatstat.random alternatives →

Recent activity from fairmodels and spatstat.random

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

  1. 20d agospatstat.randomEdge-effect-free random Dirichlet-Voronoi tessellation
  2. 2mo agospatstat.randomThree-dimensional point process simulation arrives
  3. 6mo agospatstat.randomGaussian random field generation added
  4. 9mo agofairmodelsOne-line fix in fairness_heatmap
  5. 10mo agospatstat.randomrunifdisc efficiency and fixed-count simulation options
  6. 1y agospatstat.randomConditional simulation for the cluster process generators
  7. 1y agospatstat.randomFaster rpoispp for tessellation-defined intensity
  8. 3y agofairmodelsCRAN compliance fixes and citation update
  9. 4y agofairmodelsCRAN v1.2.0
  10. 5y agofairmodelsCRAN v1.1.0
  11. 5y agofairmodelsDocumentation fixes and trimmed example runtimes
  12. 5y agofairmodelsCorrects parity_loss in the cutoff functions

Frequently asked questions

What is the difference between fairmodels and spatstat.random?

They serve adjacent needs but don't currently overlap on shipped themes. spatstat.random 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 fairmodels better than spatstat.random?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. spatstat.random 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 fairmodels?

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

What are the best alternatives to spatstat.random?

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