tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of paleobuddy and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
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.
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
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.
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
Coverage is the whole strategy, and the target has been widening from dplyr into tidyr — unnest_longer_polars(), separate_longer_delim_polars() and separate_longer_position_polars() bring list-column and string-splitting verbs that have no Polars-idiomatic equivalent in the tidyverse dialect. The other consistent thread is fidelity: distinct() dropping unselected columns, summarize() dropping the last group, relocate() honouring tidy-select helpers, NULL in mutate() behaving as dplyr does. Each of these is a small breaking change made to match the reference rather than to differ from it.
The pattern of tracking the polars floor upward every release and following tidyverse changes closely — .by in fill() arrived when tidyr 1.3.2 shipped it — suggests the next releases continue mirroring new dplyr and tidyr arguments rather than adding a distinct capability.
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 paleobuddy or tidypolars.
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 paleobuddy alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. paleobuddy and tidypolars 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. paleobuddy and tidypolars 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 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.
Top tidypolars alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypolars alternatives" section above for the current picks, or visit /alternatives/tidypolars for the full list with editorial commentary on each.