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bpbounds vs spatstat.random

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

bpbounds vs spatstat.random: at a glance

Featurebpboundsspatstat.random
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themescausal inference, instrumental variables, r, partial identificationspatial-statistics, point-processes, simulation, r-package
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is bpbounds?

bpbounds found the same swapped-cell bug twice and clamped its bounds back into range

bpbounds computes nonparametric Balke-Pearl bounds on the average causal effect from instrumental variable data, in the bivariate and trivariate cases. After years of pure packaging maintenance, the two 2026 releases are analytical corrections. Bounds on intervention probabilities are now clamped to [0, 1] so derived causal risk ratio bounds cannot fall outside their feasible range, and a cell-ordering error in the trivariate three-category instrument path has been repaired.

Read the full bpbounds 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 →

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

B
bpbounds
ANALYTICS
0.0

bpbounds found the same swapped-cell bug twice and clamped its bounds back into range

◆ Current state

bpbounds computes nonparametric Balke-Pearl bounds on the average causal effect from instrumental variable data, in the bivariate and trivariate cases. After years of pure packaging maintenance, the two 2026 releases are analytical corrections. Bounds on intervention probabilities are now clamped to [0, 1] so derived causal risk ratio bounds cannot fall outside their feasible range, and a cell-ordering error in the trivariate three-category instrument path has been repaired.

◆ Where it's heading

The direction is toward agreement with the reference Stata implementation and away from silently wrong output. The clamping change is described as matching the same fix in the Stata package, which suggests the two implementations are being reconciled rather than developed independently. The cell-ordering defect is the more instructive one: it was fixed in the calculation function in 0.1.7 and then again in the constraint matrix in 0.1.8, meaning the same x=0,y=1 / x=1,y=0 swap had been written in two places.

◆ Prediction

Since the recent fixes came from an external contributor's report and both touched the trivariate three-category path, the untested corners of that path are where further corrections would surface — but the release notes give no roadmap beyond parity with the Stata package.

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 bpbounds 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 bpbounds or spatstat.random.

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

Recent activity from bpbounds and spatstat.random

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

  1. 20d agospatstat.randomEdge-effect-free random Dirichlet-Voronoi tessellation
  2. 1mo agobpboundsbpbounds clamps probability bounds and fixes a constraint-matrix swap
  3. 2mo agospatstat.randomThree-dimensional point process simulation arrives
  4. 2mo agobpboundsbpbounds fixes swapped cells in the trivariate calculation
  5. 6mo agospatstat.randomGaussian random field generation added
  6. 10mo agospatstat.randomrunifdisc efficiency and fixed-count simulation options
  7. 1y agospatstat.randomConditional simulation for the cluster process generators
  8. 1y agospatstat.randomFaster rpoispp for tessellation-defined intensity
  9. 2y agobpboundsbpbounds 0.1.6
  10. 3y agobpboundsbpbounds 0.1.5
  11. 6y agobpboundsVersion 0.1.4 on CRAN
  12. 7y agobpboundsVersion 0.1.3

Frequently asked questions

What is the difference between bpbounds 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 bpbounds 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 bpbounds?

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