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mlr3mbo picked its defaults from a benchmark study, not from taste
Comparison · Analytics
easystats vs see
A side-by-side editorial comparison of easystats and see — release velocity, themes, recent moves, and the top alternatives to consider.
easystats vs see: at a glance
What is easystats?
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
easystats is the meta-package for the easystats ecosystem, which spans insight, parameters, performance and their siblings. It ships almost no statistics of its own; its releases add installation helpers, ecosystem introspection functions and vignettes. The consequential release in this window is 0.7.0, which moved the whole ecosystem to an MIT license.
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.
easystats vs see: editorial side-by-side
easystats
0.0ANALYTICS
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
◆ Current state
easystats is the meta-package for the easystats ecosystem, which spans insight, parameters, performance and their siblings. It ships almost no statistics of its own; its releases add installation helpers, ecosystem introspection functions and vignettes. The consequential release in this window is 0.7.0, which moved the whole ecosystem to an MIT license.
◆ Where it's heading
Work concentrates on making the ecosystem legible and installable as a unit: easystats_packages() to enumerate it, easystats_citations() to count its citations, pak and r-universe support to install it, and a complete-workflow vignette to show it in use. Underneath that, 0.7.0 settled the licensing and formalized the author list. The pattern is a project tending its own boundaries rather than adding capability.
◆ Prediction
The recent additions are all introspection and installation helpers, so the next release most likely adds another of those or refreshes component versions rather than changing what the ecosystem does.
see
0.0ANALYTICS
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 easystats 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 easystats or see.
loo
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
mlr3fselect
mlr3fselect turned feature selection into an asynchronous, distributable job
lime
lime survives on compatibility patches years after its research moment
mlr3measures
mlr3measures is systematically retrofitting sample weights across every metric
mlr3cluster
mlr3cluster went from a handful of clusterers to covering the field
See all easystats alternatives → · See all see alternatives →
Recent activity from easystats and see
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoseesee 0.14.1 adds plots for prior checks and grouped means
- 2mo agoseesee 0.14.0 renders factor loadings as node-edge graphs
- 6mo agoseesee 0.13.0 fixes reversed plot sorting, adds theme arguments
- 11mo agoseesee 0.12.0 extends normality checks to psych factor models
- 1y agoeasystatseasystats_citations() added; install_latest() gains a github source
- 1y agoseesee 0.11.0 scales theme elements with base_size
- 1y agoeasystatsComplete-workflow vignette added; install_suggested() fix
- 1y agoseesee 0.10.0 plots random-effect group levels for mixed models
- 2y agoeasystatseasystats_packages() added; pak used for installs when available
- 2y agoeasystatsR version policy vignette added
- 2y agoeasystatsFix for development package version detection
- 2y agoeasystatsEcosystem relicensed to MIT; two new authors added ⚡
Frequently asked questions
What is the difference between easystats and see?
They serve adjacent needs but don't currently overlap on shipped themes. easystats and see 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 easystats better than see?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. easystats and see 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 easystats?
Top easystats alternatives in Analytics are ranked by recent ship velocity. Browse the "easystats alternatives" section above for the current picks, or visit /alternatives/easystats 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.