n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of mrbayes and spatstat.random — release velocity, themes, recent moves, and the top alternatives to consider.
mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.
mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.
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.
mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.
The package has moved from packaging upkeep into a correctness-audit phase. 0.5.3 fixes a hardcoded three-exposure loop in MVMR-Egger reporting, a broken joint-prior branch, a sigma parameterization error in radial Egger, and several prior specifications — the profile of a maintainer reading their own model files closely rather than responding to bug reports. Platform work continues underneath: an R 4.3.0 floor inherited through a transitive dependency chain, and segfault fixes on macOS ARM.
Expect further audit-driven patches to the remaining rjags and Stan model files rather than new estimators; the fixes in 0.5.3 cluster in the Egger variants, which suggests that is where the reading is still in progress.
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.
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.
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.
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 mrbayes or spatstat.random.
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
See all mrbayes alternatives → · See all spatstat.random alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. 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.
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.
Top mrbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "mrbayes alternatives" section above for the current picks, or visit /alternatives/mrbayes for the full list with editorial commentary on each.
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.