← Back to home
Comparison · Analytics

bayestestR vs lime

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

Shared themes:r-stats

bayestestR vs lime: at a glance

FeaturebayestestRlime
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbayesian, diagnostics, stan, easystatsinterpretability, machine-learning, r-stats, maintenance
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is bayestestR?

Bayesian diagnostics get stricter defaults while the Stan backend list widens

bayestestR is the diagnostics and hypothesis-testing layer of the easystats stack, and its recent releases have concentrated on two things: reporting the right uncertainty numbers by default, and accepting posterior draws from more sources. The 0.18.x line added CmdStanFit support alongside the existing rstanarm/brms paths and switched effective-sample-size reporting to tail-ESS. Bug-fix releases in between are mostly CRAN-check maintenance.

Read the full bayestestR trajectory →

What is lime?

lime survives on compatibility patches years after its research moment

lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.

Read the full lime trajectory →

bayestestR vs lime: editorial side-by-side

B
bayestestR
ANALYTICS
0.0

Bayesian diagnostics get stricter defaults while the Stan backend list widens

◆ Current state

bayestestR is the diagnostics and hypothesis-testing layer of the easystats stack, and its recent releases have concentrated on two things: reporting the right uncertainty numbers by default, and accepting posterior draws from more sources. The 0.18.x line added CmdStanFit support alongside the existing rstanarm/brms paths and switched effective-sample-size reporting to tail-ESS. Bug-fix releases in between are mostly CRAN-check maintenance.

◆ Where it's heading

The package is converging on a single posture: work with raw MCMC draws from anywhere, and report the diagnostic that actually governs the interval being shown. Successive releases have swapped defaults rather than added surface area, and the efficiency work in 0.16.x aimed squarely at large brms and rstanarm fits. Output formatting is drifting toward the shared easystats display() and tinytable path.

◆ Prediction

Expect continued backend coverage on the Stan side and further alignment of print/display behavior with insight and the rest of easystats; the entries do not show a push into new inference methods.

L
lime
ANALYTICS
0.0

lime survives on compatibility patches years after its research moment

◆ Current state

lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.

◆ Where it's heading

The package is in custodial maintenance — kept installable and compatible with the model packages it explains, rather than developed. The 2022 handover is the most consequential entry in the window because it determined that the package would keep getting patches at all.

◆ Prediction

Expect the next release to be another compatibility fix triggered by an upstream model package, not new explanation methods.

Alternatives to bayestestR and lime

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 bayestestR or lime.

See all bayestestR alternatives → · See all lime alternatives →

Recent activity from bayestestR and lime

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

  1. 2mo agobayestestRmcse() gains a centrality argument
  2. 2mo agobayestestRCmdStanFit support and tail-ESS as the default diagnostic
  3. 8mo agolimeCompatibility across all xgboost versions
  4. 11mo agobayestestRrope() gains complement probabilities; display() methods added
  5. 1y agobayestestRdescribe_posterior() efficiency and multinomial handling
  6. 1y agobayestestReffects argument changes behavior for large brms/rstanarm fits
  7. 1y agobayestestRTail ESS returned from effective_sample() and its callers
  8. 3y agolimeMaintainer handover to Emil Hvitfeldt
  9. 5y agolimeorder() fix and lighter dependencies
  10. 6y agolimeNamespace fix following glmnet changes
  11. 7y agolimeexplain() gains pass-through args and gower_pow tuning
  12. 8y agolimeh2o support, NA handling and date feature types

Frequently asked questions

What is the difference between bayestestR and lime?

Both compete on the same themes — r-stats — within Analytics. bayestestR and lime 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 bayestestR better than lime?

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

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

What are the best alternatives to lime?

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