rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
bbotk vs modelbased
A side-by-side editorial comparison of bbotk and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
bbotk vs modelbased: at a glance
What is bbotk?
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
bbotk is the black-box optimization backend behind mlr3 tuning: search spaces, terminators, archives, and an async layer built on rush. Recent releases pair steady async-API buildout with removal of the deprecated arguments that preceded it. The 1.9.0 release introduced EvalInstance as a base class for OptimInstance, separating evaluating an objective from optimizing one.
What is modelbased?
modelbased is turning marginal effects into a full contrast grammar
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
bbotk vs modelbased: editorial side-by-side
bbotk
2.5ANALYTICS
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
◆ Current state
bbotk is the black-box optimization backend behind mlr3 tuning: search spaces, terminators, archives, and an async layer built on rush. Recent releases pair steady async-API buildout with removal of the deprecated arguments that preceded it. The 1.9.0 release introduced EvalInstance as a base class for OptimInstance, separating evaluating an objective from optimizing one.
◆ Where it's heading
Two threads run through the visible history. The first is async optimization maturing: ArchiveAsync gained a full push/finish/fail vocabulary over rush tasks in 1.11.0, and 1.12.0 deleted the deprecated extra arguments it replaced. The second is dependency consolidation, with custom C hypervolume code handed to moocore and rush pinned to 1.0.0, trimming maintenance surface as the async path becomes the default.
◆ Prediction
The deprecation removals in 1.12.0 suggest the async archive API is now treated as settled; the next releases most likely build on EvalInstance rather than continuing to churn ArchiveAsync.
modelbased
0.0ANALYTICS
modelbased is turning marginal effects into a full contrast grammar
◆ Current state
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
◆ Where it's heading
The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.
◆ Prediction
With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.
Alternatives to bbotk and modelbased
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 bbotk or modelbased.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
See all bbotk alternatives → · See all modelbased alternatives →
Recent activity from bbotk and modelbased
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 24d agobbotkDeprecated extra argument removed from ArchiveAsync methods
- 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
- 1mo agobbotkArchiveAsync gains full push/finish/fail task API over rush
- 2mo agobbotkDominance and hypervolume computation moved to moocore
- 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
- 4mo agobbotkmlr_test_functions adds standard optimization benchmarks
- 5mo agobbotkEvalInstance base class separates evaluation from optimization ⚡
- 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
- 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
- 8mo agobbotkFix: conditions now work with OptimizerLocalSearch
- 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
Frequently asked questions
What is the difference between bbotk and modelbased?
They serve adjacent needs but don't currently overlap on shipped themes. bbotk is currently shipping more aggressively (velocity 2.5 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.
Is bbotk better than modelbased?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bbotk is currently shipping more aggressively (velocity 2.5 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.
What are the best alternatives to bbotk?
Top bbotk alternatives in Analytics are ranked by recent ship velocity. Browse the "bbotk alternatives" section above for the current picks, or visit /alternatives/bbotk for the full list with editorial commentary on each.
What are the best alternatives to modelbased?
Top modelbased alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbased alternatives" section above for the current picks, or visit /alternatives/modelbased for the full list with editorial commentary on each.