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ggeffects vs rgbif

A side-by-side editorial comparison of ggeffects and rgbif — release velocity, themes, recent moves, and the top alternatives to consider.

ggeffects vs rgbif: at a glance

Featureggeffectsrgbif
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmarginal-effects, r-stats, statistics, breaking-changesgbif, biodiversity-data, bulk-downloads, sql-queries
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is ggeffects?

ggeffects hands its contrast engine to modelbased and keeps the interface

ggeffects computes and plots marginal effects for a long tail of R model classes. Its recent line has two threads: steadily broadening model support and argument surface, and repeatedly absorbing breaking changes from the packages it computes on top of. In 2.2.0 it stopped absorbing them and delegated test_predictions() and johnson_neyman() to modelbased instead.

Read the full ggeffects trajectory →

What is rgbif?

rgbif is steadily pushing users off paged searching and onto real downloads.

rgbif ships several times a year and the recent releases cluster around downloads. 3.8.1 added `occ_download_sql()` for SQL-based occurrence downloads; 3.8.2 added DOI-to-download-key resolution and institutionKey downloads; 3.8.3 relayed GBIF's new throttling of bulk paging through `occ_search()` with a message pointing users at `occ_download()`; 3.8.5 added a family of `occ_download_stats_*()` functions plus multiple-taxonomy and verbatim-extension downloads. Alongside that, `name_backbone()` moved to GBIF API v2, and 3.8.0 soft-deprecated `occ_data()`.

Read the full rgbif trajectory →

ggeffects vs rgbif: editorial side-by-side

G
ggeffects
ANALYTICS
0.0

ggeffects hands its contrast engine to modelbased and keeps the interface

◆ Current state

ggeffects computes and plots marginal effects for a long tail of R model classes. Its recent line has two threads: steadily broadening model support and argument surface, and repeatedly absorbing breaking changes from the packages it computes on top of. In 2.2.0 it stopped absorbing them and delegated test_predictions() and johnson_neyman() to modelbased instead.

◆ Where it's heading

The package is settling into a front-end role — a consistent predict_response() interface over other people's estimation engines — rather than owning the computation itself. The 2.x releases also show a pattern of removing deprecated arguments and clarifying mixed-model semantics, so the interface is being tightened as the backend is outsourced.

◆ Prediction

Expect the features lost in the modelbased handover to return as that package's contrast and slope estimation matures, rather than being reimplemented locally.

R
rgbif
ANALYTICS
0.0

rgbif is steadily pushing users off paged searching and onto real downloads.

◆ Current state

rgbif ships several times a year and the recent releases cluster around downloads. 3.8.1 added `occ_download_sql()` for SQL-based occurrence downloads; 3.8.2 added DOI-to-download-key resolution and institutionKey downloads; 3.8.3 relayed GBIF's new throttling of bulk paging through `occ_search()` with a message pointing users at `occ_download()`; 3.8.5 added a family of `occ_download_stats_*()` functions plus multiple-taxonomy and verbatim-extension downloads. Alongside that, `name_backbone()` moved to GBIF API v2, and 3.8.0 soft-deprecated `occ_data()`.

◆ Where it's heading

Two things are happening at once. GBIF is discouraging bulk retrieval through the search API, and rgbif is building out the download path fast enough to absorb the traffic — SQL queries, DOI round-tripping, format description, and now statistics about the downloads themselves. Metadata coverage has expanded in parallel, with a dozen `dataset_*()` functions in 3.7.9 and GRSciColl institution search in 3.8.3. The deprecations are consistent: `occ_data()`, `occ_facet()`, `occ_count(type=)` all retired in favour of narrower replacements.

◆ Prediction

The download surface is where the next additions will land — likely more SQL-download tooling and further statistics endpoints, following 3.8.1 and 3.8.5.

Alternatives to ggeffects and rgbif

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 ggeffects or rgbif.

See all ggeffects alternatives → · See all rgbif alternatives →

Recent activity from ggeffects and rgbif

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 4mo agorgbifrgbif 3.8.5 adds occurrence download statistics functions
  2. 8mo agorgbifrgbif 3.8.4 moves name matching to GBIF API v2
  3. 11mo agorgbifrgbif 3.8.3 adds GRSciColl search, relays GBIF paging throttle
  4. 1y agorgbifrgbif 3.8.2 resolves download DOIs to keys
  5. 1y agoggeffectsggeffects delegates contrasts and slopes to modelbased
  6. 1y agoggeffectsFive focal terms and formula-based contrast tests
  7. 1y agoggeffectsMixed-model predictions split type from interval
  8. 1y agoggeffectsBias correction for back-transformed mixed-model predictions
  9. 1y agorgbifrgbif 3.8.1 adds SQL-based occurrence downloads
  10. 1y agoggeffectsSupport for WeightIt model classes
  11. 2y agoggeffectsglmgee support and vcov controls for ggemmeans()
  12. 2y agorgbifrgbif 3.8.0 soft-deprecates occ_data(), adds download describe

Frequently asked questions

What is the difference between ggeffects and rgbif?

They serve adjacent needs but don't currently overlap on shipped themes. ggeffects and rgbif 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 ggeffects better than rgbif?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggeffects and rgbif 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 ggeffects?

Top ggeffects alternatives in Analytics are ranked by recent ship velocity. Browse the "ggeffects alternatives" section above for the current picks, or visit /alternatives/ggeffects for the full list with editorial commentary on each.

What are the best alternatives to rgbif?

Top rgbif alternatives in Analytics are ranked by recent ship velocity. Browse the "rgbif alternatives" section above for the current picks, or visit /alternatives/rgbif for the full list with editorial commentary on each.