ANALYTICS
mlr3mbo picked its defaults from a benchmark study, not from taste
Alternatives · analytics tools
ggeffects alternatives
The best ggeffects alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 13, 2026
Looking for the best alternatives to ggeffects? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, ggeffects shipped 0 meaningful updates in the last 30 days and carries a velocity score of 0.0 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.
About 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.
Velocity 0.0 · Last update 58m ago
Top 12 alternatives to ggeffects
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
ANALYTICS
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
ANALYTICS
comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
ANALYTICS
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
ANALYTICS
patchwork stopped being a ggplot composer and became a page composer.
ANALYTICS
mlr3fselect turned feature selection into an asynchronous, distributable job
ANALYTICS
lime survives on compatibility patches years after its research moment
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mlr3measures is systematically retrofitting sample weights across every metric
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mlr3cluster went from a handful of clusterers to covering the field
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mlr3filters grows one feature-selection filter at a time
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mlr3learners spends its releases absorbing upstream churn
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gutenbergr has been rebuilt around caching and mirror resilience
ggeffects vs alternatives — shipping velocity at a glance
Velocity score (0–10) and meaningful releases shipped in the last 30 days, from official changelogs. Higher = shipping faster.
| Product | Velocity | Sparks · 30d | Focus areas | Latest release |
|---|---|---|---|---|
| ggeffects (baseline) | 0.0 | 0 | marginal-effectsr-statsstatistics | ggeffects delegates contrasts and slopes to modelbased |
| mlr3mbo | 2.5 | 0 | bayesian-optimizationmlr3hyperparameter-tuning | mlr3mbo 1.0.0 ships benchmark-derived default settings |
| loo | 2.5 | 0 | bayesiancross-validationstan | loo_compare returns a data.frame with new uncertainty columns |
| comtradr | 2.5 | 0 | trade dataapi wrapperun comtrade | — |
| bbotk | 2.5 | 0 | black-box optimizationmlr3async execution | EvalInstance base class separates evaluation from optimization |
| patchwork | 0.0 | 0 | ggplot2compositiontables | gt tables become first-class patchwork objects |
| mlr3fselect | 0.0 | 0 | feature-selectionmlr3machine-learning | Asynchronous feature selection arrives with FSelectorAsync |
| lime | 0.0 | 0 | interpretabilitymachine-learningr-stats | — |
| mlr3measures | 0.0 | 0 | metricsmlr3machine-learning | — |
| mlr3cluster | 0.0 | 0 | clusteringmlr3machine-learning | Nine new clustering learners in one release |
| mlr3filters | 0.0 | 0 | feature-selectionmlr3machine-learning | — |
| mlr3learners | 0.0 | 0 | mlr3machine-learningr-stats | — |
| gutenbergr | 0.0 | 0 | text-miningr-statscaching | — |
The 12 best ggeffects alternatives, in depth
1. mlr3mbo · velocity 2.5
Mlr3mbo picked its defaults from a benchmark study, not from taste.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “mlr3mbo 1.0.0 ships benchmark-derived default settings”.
Where ggeffects leans on marginal effects, r stats and statistics, mlr3mbo focuses on bayesian optimization, mlr3 and hyperparameter tuning.
mlr3mbo and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
2. loo · velocity 2.5
Loo keeps rewriting the diagnostics Bayesian modellers read off model comparison.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “loo_compare returns a data.frame with new uncertainty columns”.
Where ggeffects leans on marginal effects, r stats and statistics, loo focuses on bayesian, cross validation and stan.
loo and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
3. comtradr · velocity 2.5
Comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where ggeffects leans on marginal effects, r stats and statistics, comtradr focuses on trade data, api wrapper and un comtrade.
comtradr and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full comtradr trajectory → · Compare ggeffects vs comtradr →
4. bbotk · velocity 2.5
Bbotk is generalizing from an optimizer toolkit into an evaluation framework.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “EvalInstance base class separates evaluation from optimization”.
Where ggeffects leans on marginal effects, r stats and statistics, bbotk focuses on black box optimization, mlr3 and async execution.
bbotk and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
5. patchwork · velocity 0.0
Patchwork stopped being a ggplot composer and became a page composer.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “gt tables become first-class patchwork objects”.
Where ggeffects leans on marginal effects, r stats and statistics, patchwork focuses on ggplot2, composition and tables.
patchwork and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full patchwork trajectory → · Compare ggeffects vs patchwork →
6. mlr3fselect · velocity 0.0
Mlr3fselect turned feature selection into an asynchronous, distributable job.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Asynchronous feature selection arrives with FSelectorAsync”.
Where ggeffects leans on marginal effects, r stats and statistics, mlr3fselect focuses on feature selection, mlr3 and machine learning.
mlr3fselect and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3fselect trajectory → · Compare ggeffects vs mlr3fselect →
7. lime · velocity 0.0
Lime survives on compatibility patches years after its research moment.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggeffects leans on marginal effects, r stats and statistics, lime focuses on interpretability, machine learning and r stats.
lime and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
8. mlr3measures · velocity 0.0
Mlr3measures is systematically retrofitting sample weights across every metric.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggeffects leans on marginal effects, r stats and statistics, mlr3measures focuses on metrics, mlr3 and machine learning.
mlr3measures and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3measures trajectory → · Compare ggeffects vs mlr3measures →
9. mlr3cluster · velocity 0.0
Mlr3cluster went from a handful of clusterers to covering the field.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Nine new clustering learners in one release”.
Where ggeffects leans on marginal effects, r stats and statistics, mlr3cluster focuses on clustering, mlr3 and machine learning.
mlr3cluster and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3cluster trajectory → · Compare ggeffects vs mlr3cluster →
10. mlr3filters · velocity 0.0
Mlr3filters grows one feature-selection filter at a time.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggeffects leans on marginal effects, r stats and statistics, mlr3filters focuses on feature selection, mlr3 and machine learning.
mlr3filters and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3filters trajectory → · Compare ggeffects vs mlr3filters →
11. mlr3learners · velocity 0.0
Mlr3learners spends its releases absorbing upstream churn.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggeffects leans on marginal effects, r stats and statistics, mlr3learners focuses on mlr3, machine learning and r stats.
mlr3learners and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3learners trajectory → · Compare ggeffects vs mlr3learners →
12. gutenbergr · velocity 0.0
Gutenbergr has been rebuilt around caching and mirror resilience.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggeffects leans on marginal effects, r stats and statistics, gutenbergr focuses on text mining, r stats and caching.
gutenbergr and ggeffects have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full gutenbergr trajectory → · Compare ggeffects vs gutenbergr →
Frequently asked questions
What are the best alternatives to ggeffects?
The top ggeffects alternatives we currently track in analytics tools are mlr3mbo, loo, comtradr, bbotk, patchwork, ranked by recent ship velocity.
How is this list of ggeffects alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare ggeffects directly with one of these alternatives?
Yes — every card has a "Compare with ggeffects" link to a side-by-side /compare page.