rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of mizer and RadialMR — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | mizer | RadialMR |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 5.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | size-spectrum-modelling, marine-ecology, numerical-methods, extension-framework | mendelian-randomization, radial-plots, correctness-audit, statistical-inference |
| Last editorial update | 50m ago | 1h ago |
| Website | Visit → | Visit → |
After two and a half years dormant, mizer shipped three major versions in seven weeks.
The size-spectrum fish modelling package sat at 2.5.0 from December 2023 until June 2026, then released 3.0.0, 3.1.0 and 3.2.0 in the space of seven weeks. The three releases divide cleanly: 3.0.0 added biological realism through a diffusion term in the McKendrick-von Foerster equation, 3.1.0 added an opt-in second-order numerical scheme in size, and 3.2.0 rebuilt how species and resource parameters are set. Backward compatibility is handled carefully throughout — the experimental scheme is off by default and the first-order path is byte-identical to previous versions.
RadialMR's 2026 release corrects degrees of freedom that had been wrong since documentation.
RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().
The size-spectrum fish modelling package sat at 2.5.0 from December 2023 until June 2026, then released 3.0.0, 3.1.0 and 3.2.0 in the space of seven weeks. The three releases divide cleanly: 3.0.0 added biological realism through a diffusion term in the McKendrick-von Foerster equation, 3.1.0 added an opt-in second-order numerical scheme in size, and 3.2.0 rebuilt how species and resource parameters are set. Backward compatibility is handled carefully throughout — the experimental scheme is off by default and the first-order path is byte-identical to previous versions.
Two threads run through the 3.x line. The first is numerical: diffusion, then higher-order accuracy in both size and time, with explicit warnings that enabling them shifts diagnostics and may require recalibration. The second is making the package composable — extensions now work regardless of load order, and parameter assignment propagates to the derived rate arrays instead of being silently discarded. That second thread reads as the more consequential one: the 3.2.0 notes describe scalar edits that previously vanished and now accumulate, which is the kind of fix that changes what published model configurations actually computed.
Expect the experimental second-order scheme to move toward default-on once recalibration guidance exists, and the patch line to keep absorbing the documentation and website gaps that 3.2.1 started on.
RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().
This is a package being read closely by its maintainer rather than extended. The 1.2.x line pairs statistical corrections with defensive hardening — an rmr_format class check so unformatted input fails with a clear message, and plotly_radial() dispatching on object class instead of counting list elements. Both are the kind of change made while auditing, not while building.
Expect the audit to continue into the remaining estimator internals and print methods rather than new radial variants; the entries show no feature work queued.
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 mizer or RadialMR.
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See all mizer alternatives → · See all RadialMR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. mizer is currently shipping more aggressively (velocity 5.0 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. mizer is currently shipping more aggressively (velocity 5.0 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 mizer alternatives in Analytics are ranked by recent ship velocity. Browse the "mizer alternatives" section above for the current picks, or visit /alternatives/mizer-r for the full list with editorial commentary on each.
Top RadialMR alternatives in Analytics are ranked by recent ship velocity. Browse the "RadialMR alternatives" section above for the current picks, or visit /alternatives/radialmr for the full list with editorial commentary on each.