qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of lpjmlkit and tern.rbmi — release velocity, themes, recent moves, and the top alternatives to consider.
The LPJmL toolkit finally reads NetCDF, closing a gap against the format its field uses.
lpjmlkit is the R toolkit for running the LPJmL dynamic global vegetation model and reading its output. The 1.8.0 release adds direct NetCDF reading, either straight or via .nc.json metafiles, alongside the package's own binary formats. Before that, 1.7.3 sped up read_io(), reworked the LPJmLGridData implementation and added reservoir input support. Releases are infrequent, roughly one every 12 to 18 months.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window, and the three older entries now backfilled are version-bump automation.
lpjmlkit is the R toolkit for running the LPJmL dynamic global vegetation model and reading its output. The 1.8.0 release adds direct NetCDF reading, either straight or via .nc.json metafiles, alongside the package's own binary formats. Before that, 1.7.3 sped up read_io(), reworked the LPJmLGridData implementation and added reservoir input support. Releases are infrequent, roughly one every 12 to 18 months.
The work concentrates on the I/O layer rather than the modeling interface, and it is moving toward the formats the wider earth-system community already exchanges. The gap between 1.7.3 and 1.8.0 is over a year, so this is a research-group package released when the science requires it, not on a schedule. The changelog itself is thin — several entries are merge-commit text or CRAN resubmissions.
Further I/O breadth is the likeliest direction now that NetCDF is supported, though the entries give no schedule; the release cadence has not been regular enough to predict timing.
tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window, and the three older entries now backfilled are version-bump automation.
This is a thin adapter package and behaves like one — it moves when CRAN or an upstream dependency forces it to. Between 2022 and 2024 the feed shows only version bumps, and the 2025 releases are packaging concerns rather than analysis changes. The newly surfaced 2022 entries reinforce rather than change that reading.
Expect the next release to be triggered by a CRAN check failure or an {rbmi} update rather than by new tabulation features.
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 lpjmlkit or tern.rbmi.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all lpjmlkit alternatives → · See all tern.rbmi alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. lpjmlkit and tern.rbmi 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. lpjmlkit and tern.rbmi 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 lpjmlkit alternatives in Analytics are ranked by recent ship velocity. Browse the "lpjmlkit alternatives" section above for the current picks, or visit /alternatives/lpjmlkit-r for the full list with editorial commentary on each.
Top tern.rbmi alternatives in Analytics are ranked by recent ship velocity. Browse the "tern.rbmi alternatives" section above for the current picks, or visit /alternatives/tern-rbmi for the full list with editorial commentary on each.