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loo vs see

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

loo vs see: at a glance

Featureloosee
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesbayesian, cross-validation, stan, r-statsr, easystats, data-visualization, ggplot2
Last editorial update1h ago5h ago
WebsiteVisit →Visit →

What is loo?

loo keeps rewriting the diagnostics Bayesian modellers read off model comparison

loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.

Read the full loo trajectory →

What is see?

see grows wherever easystats adds a diagnostic, one plot method at a time.

see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.

Read the full see trajectory →

loo vs see: editorial side-by-side

L
loo
ANALYTICS
2.5

loo keeps rewriting the diagnostics Bayesian modellers read off model comparison

◆ Current state

loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.

◆ Where it's heading

The package is being brought in line with the current PSIS literature rather than extended with new features, and the practical effect is that the numbers practitioners quote in papers keep changing meaning. Work is increasingly delegated to posterior for shared computations, and the project has added contributor process, benchmarks and a published AI contribution policy.

◆ Prediction

Expect further work on comparison diagnostics — the p_worse and diag_* columns are new enough that their defaults and documentation will likely be revised next.

S
see
ANALYTICS
0.0

see grows wherever easystats adds a diagnostic, one plot method at a time.

◆ Current state

see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.

◆ Where it's heading

Growth here is downstream-driven rather than self-directed: see expands to cover new diagnostics as easystats produces them. Running alongside that is a sustained investment in presentation control — theme arguments on plot methods, elements that scale with base_size — which suits users embedding these plots in documents rather than glancing at them interactively.

◆ Prediction

Expect new plot methods to keep arriving in step with performance and parameters releases, with continued theming work rather than any change in the package's scope.

Alternatives to loo and see

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 loo or see.

See all loo alternatives → · See all see alternatives →

Recent activity from loo and see

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

  1. 20d agoloopsis_smooth_tail revert and simplify arg restored
  2. 1mo agoseesee 0.14.1 adds plots for prior checks and grouped means
  3. 1mo agolooloo_compare returns a data.frame with new uncertainty columns
  4. 2mo agoseesee 0.14.0 renders factor loadings as node-edge graphs
  5. 6mo agoseesee 0.13.0 fixes reversed plot sorting, adds theme arguments
  6. 7mo agolooStacking overflow fixes and posterior-based ESS
  7. 11mo agoseesee 0.12.0 extends normality checks to psych factor models
  8. 1y agoseesee 0.11.0 scales theme elements with base_size
  9. 1y agoseesee 0.10.0 plots random-effect group levels for mixed models
  10. 2y agolooMore robust Pareto-k diagnostics and moment matching
  11. 2y agolooPareto-k thresholds now depend on sample size
  12. 3y agolooLOO predictive metrics and CRPS scoring functions

Frequently asked questions

What is the difference between loo and see?

They serve adjacent needs but don't currently overlap on shipped themes. loo 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 loo better than see?

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

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

What are the best alternatives to see?

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