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OneSampleMR vs spatstat.random

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

OneSampleMR vs spatstat.random: at a glance

FeatureOneSampleMRspatstat.random
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesmendelian randomization, r, instrumental variables, epidemiologyspatial-statistics, point-processes, simulation, r-package
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is OneSampleMR?

OneSampleMR found that argument order in a formula was silently changing its estimates

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

Read the full OneSampleMR 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 →

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

O
OneSampleMR
ANALYTICS
0.0

OneSampleMR found that argument order in a formula was silently changing its estimates

◆ Current state

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

◆ Where it's heading

Two threads. The first is reach — fsw() now reads models fitted by AER::ivreg(), estimatr::iv_robust() and fixest::feols() in addition to ivreg::ivreg(), which makes conditional F statistics available without refitting in the package's own idiom. The second is hardening: clear errors when more than one exposure is given or when a variable collides with the reserved name y, and print methods that no longer fail on user-specified t0 with log or logit links. Both come largely from user reports rather than a plan.

◆ Prediction

The estimator-support work has been adding one IV-fitting package at a time on outside contributions, so further backends are the likeliest next content — the package's own estimators have been stable since first release.

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 OneSampleMR 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 OneSampleMR or spatstat.random.

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

Recent activity from OneSampleMR 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 agoOneSampleMROneSampleMR fixes estimates broken by covariate order in the formula
  3. 2mo agospatstat.randomThree-dimensional point process simulation arrives
  4. 5mo agoOneSampleMROneSampleMR computes conditional F for three more IV packages
  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 agoOneSampleMROneSampleMR 0.1.6
  9. 1y agospatstat.randomFaster rpoispp for tessellation-defined intensity
  10. 2y agoOneSampleMROneSampleMR 0.1.5
  11. 2y agoOneSampleMROneSampleMR 0.1.4
  12. 3y agoOneSampleMROneSampleMR 0.1.3

Frequently asked questions

What is the difference between OneSampleMR 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 OneSampleMR 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 OneSampleMR?

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