n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of citeme and mrbayes — release velocity, themes, recent moves, and the top alternatives to consider.
Citation metadata machinery breaks out of INBO's checklist package to stand on its own.
citeme handles citation metadata for research software and organisations — building citation files, validating ORCIDs, RORs, licenses and URLs, and prompting for the pieces interactively. It was extracted from the checklist package in 0.1.0 and has spent the four releases since fleshing out organisational roles, most visibly publishers.
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.
citeme handles citation metadata for research software and organisations — building citation files, validating ORCIDs, RORs, licenses and URLs, and prompting for the pieces interactively. It was extracted from the checklist package in 0.1.0 and has spent the four releases since fleshing out organisational roles, most visibly publishers.
Development is running in tight monthly increments along two tracks: modelling who is attached to a piece of research software, and smoothing the interactive prompts that collect it. The publisher role added in 0.1.1 propagated through validation, community detection and YAML handling over the next two releases, which is how this package tends to land a concept — introduce the class field, then follow it everywhere it needs to reach.
Expect the interactive ask_* family to keep growing alongside whatever metadata field is being modelled next, and further alignment with the checklist package it was carved out of.
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.
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 citeme or mrbayes.
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 citeme alternatives → · See all mrbayes alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. citeme and mrbayes 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. citeme and mrbayes 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.
Top citeme alternatives in Analytics are ranked by recent ship velocity. Browse the "citeme alternatives" section above for the current picks, or visit /alternatives/citeme-r for the full list with editorial commentary on each.
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.