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desirability2 vs insight

A side-by-side editorial comparison of desirability2 and insight — release velocity, themes, recent moves, and the top alternatives to consider.

desirability2 vs insight: at a glance

Featuredesirability2insight
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestidymodels, multi-objective optimization, model selection, desirability functionsmodel-introspection, easystats, bayesian, performance
Last editorial update53m ago2h ago
WebsiteVisit →Visit →

What is desirability2?

desirability2 is making multi-metric model selection a first-class tidymodels step.

desirability2 implements desirability functions, which map several metrics onto a common 0-1 scale so they can be combined into a single objective. The package is young: three releases, the first of which only added a NEWS file. Its substance arrived in 0.1.0 with hooks into tidymodels' tune package.

Read the full desirability2 trajectory →

What is insight?

insight quietly widens the set of model objects the easystats ecosystem can read

insight is the extraction layer under the easystats packages — it answers what a fitted model's parameters, data, variance and priors are, for whatever object it is handed. The 1.4.x and 1.5.x releases read as a steady widening of that support list: tidymodels workflows, cmdstanr fits, rstpm2 survival models, lavaan variance-covariance, mice imputations.

Read the full insight trajectory →

desirability2 vs insight: editorial side-by-side

D
desirability2
ANALYTICS
0.0

desirability2 is making multi-metric model selection a first-class tidymodels step.

◆ Current state

desirability2 implements desirability functions, which map several metrics onto a common 0-1 scale so they can be combined into a single objective. The package is young: three releases, the first of which only added a NEWS file. Its substance arrived in 0.1.0 with hooks into tidymodels' tune package.

◆ Where it's heading

The direction is integration rather than standalone use. Version 0.1.0 added select_best_desirability() and show_best_desirability() to resolve a tuning run against several metrics at once; 0.2.0 exported make_desirability_cols() so other packages can build on it and made data-driven limits the default, removing the need to state ranges by hand. Both releases move work from the user into the package.

◆ Prediction

The exported helper and the developer-facing desirability() API point to adoption by other tidymodels packages as the next step rather than new functionality here.

I
insight
ANALYTICS
0.0

insight quietly widens the set of model objects the easystats ecosystem can read

◆ Current state

insight is the extraction layer under the easystats packages — it answers what a fitted model's parameters, data, variance and priors are, for whatever object it is handed. The 1.4.x and 1.5.x releases read as a steady widening of that support list: tidymodels workflows, cmdstanr fits, rstpm2 survival models, lavaan variance-covariance, mice imputations.

◆ Where it's heading

Two things move together here. The support list grows toward objects produced outside the easystats world, and performance work targets the helpers that everything else calls — compact_list(), is_empty_object(), find_parameters() on mgcv models. New functions appear occasionally (get_simulated(), vcovFPC()) but the center of gravity is coverage, not capability.

◆ Prediction

Expect further model classes to be added as downstream easystats packages need them, and continued alignment with R-devel behavior changes like the weighted-residuals revision.

Alternatives to desirability2 and insight

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 desirability2 or insight.

See all desirability2 alternatives → · See all insight alternatives →

Recent activity from desirability2 and insight

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

  1. 1mo agoinsightcompact_list() performance and lavaan variance-covariance support
  2. 2mo agoinsightcmdstanr support and finite-population-corrected variance
  3. 4mo agoinsightget_simulated() added; rstpm2 survival models supported
  4. 6mo agoinsightWeighted residuals revised to match R 4.6.0
  5. 6mo agoinsighttidymodels workflow objects become readable
  6. 8mo agoinsightlme4 convergence and fixest data extraction fixes
  7. 11mo agodesirability2make_desirability_cols() exported; data-driven limits on by default
  8. 1y agodesirability2Desirability-based model selection added for tune
  9. 3y agodesirability2NEWS.md added to track package changes

Frequently asked questions

What is the difference between desirability2 and insight?

They serve adjacent needs but don't currently overlap on shipped themes. desirability2 and insight 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 desirability2 better than insight?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. desirability2 and insight 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 desirability2?

Top desirability2 alternatives in Analytics are ranked by recent ship velocity. Browse the "desirability2 alternatives" section above for the current picks, or visit /alternatives/desirability2 for the full list with editorial commentary on each.

What are the best alternatives to insight?

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