tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of lpjmlkit and paleobuddy — 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.
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
paleobuddy simulates diversification, fossil records and phylogenetic trees, with rates that can be arbitrary functions of time — its founding idea, implemented through rexp.var() generalizing exponential and Weibull draws. The 1.1.0 release adds state-dependent speciation and extinction simulation at roughly MuHiSSE generality, and lets simulations stop at a target number of extant species instead of conditioning on time.
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.
paleobuddy simulates diversification, fossil records and phylogenetic trees, with rates that can be arbitrary functions of time — its founding idea, implemented through rexp.var() generalizing exponential and Weibull draws. The 1.1.0 release adds state-dependent speciation and extinction simulation at roughly MuHiSSE generality, and lets simulations stop at a target number of extant species instead of conditioning on time.
Releases track the maintainer's publications rather than a product cadence — 1.0.0 accompanied the MEE manuscript, 1.0.0.1 exists purely as a Zenodo citation anchor, and 1.1.0 is stated as going with a paper on SSE model accuracy for trees including fossil data. That framing sets the direction: the package grows whichever capability the next study needs to test. The stated SSE limits, no quantitative traits and no cladogenetic transitions, mark exactly where that boundary currently sits.
Quantitative traits and cladogenetic transitions are named as missing, which makes them the obvious next targets, though on this history the timing will follow a paper rather than a roadmap.
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 paleobuddy.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
A single-purpose ggplot2 inset tool, refining the same three arguments.
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
gtfstools stopped guarding its own object model and started accepting everyone else's.
The glue package that makes R carry units and uncertainty through the same calculation.
See all lpjmlkit alternatives → · See all paleobuddy 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 paleobuddy 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 paleobuddy 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 paleobuddy alternatives in Analytics are ranked by recent ship velocity. Browse the "paleobuddy alternatives" section above for the current picks, or visit /alternatives/paleobuddy for the full list with editorial commentary on each.