rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
gutenbergr vs modelbased
A side-by-side editorial comparison of gutenbergr and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
gutenbergr vs modelbased: at a glance
What is gutenbergr?
gutenbergr has been rebuilt around caching and mirror resilience
gutenbergr downloads Project Gutenberg texts into R. Its recent releases are a sustained reliability push driven largely by one contributor: a download cache with its own function family, mirror discovery with a known-good fallback, a User-Agent string identifying the client, and a section-marker helper. The newest releases are narrow compatibility and duplication fixes on top of that base.
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.
gutenbergr vs modelbased: editorial side-by-side
gutenbergr
0.0ANALYTICS
gutenbergr has been rebuilt around caching and mirror resilience
◆ Current state
gutenbergr downloads Project Gutenberg texts into R. Its recent releases are a sustained reliability push driven largely by one contributor: a download cache with its own function family, mirror discovery with a known-good fallback, a User-Agent string identifying the client, and a section-marker helper. The newest releases are narrow compatibility and duplication fixes on top of that base.
◆ Where it's heading
Development is aimed squarely at the failure modes of depending on a volunteer-run mirror network — cache locally, degrade gracefully when the mirror list cannot be parsed, and identify yourself politely to the servers. The version sequence in this feed is not monotonic, so recency here follows publication date rather than version number.
◆ Prediction
Further work should continue along the caching and mirror-handling line, with dataset refreshes as the Gutenberg catalogue changes.
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 gutenbergr 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 gutenbergr 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 gutenbergr alternatives → · See all modelbased alternatives →
Recent activity from gutenbergr and modelbased
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
- 1mo agogutenbergrMirror listing adapted to readMDTable 0.4.0
- 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
- 3mo agogutenbergrFixed duplicated lines for multi-author works
- 4mo agogutenbergrMirror selection now uses the published mirror list
- 5mo agogutenbergrSection markers, a User-Agent string and usage vignettes
- 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
- 6mo agogutenbergrMirror fallback instead of hard errors
- 7mo agogutenbergrDownloads are now cached, with a cache management API
- 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
- 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 gutenbergr and modelbased?
They serve adjacent needs but don't currently overlap on shipped themes. gutenbergr and modelbased 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.
Is gutenbergr better than modelbased?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gutenbergr and modelbased 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.
What are the best alternatives to gutenbergr?
Top gutenbergr alternatives in Analytics are ranked by recent ship velocity. Browse the "gutenbergr alternatives" section above for the current picks, or visit /alternatives/gutenbergr 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.