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discrim vs insight

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

discrim vs insight: at a glance

Featurediscriminsight
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestidymodels, discriminant analysis, parsnip extension, classificationmodel-introspection, easystats, bayesian, performance
Last editorial update53m ago2h ago
WebsiteVisit →Visit →

What is discrim?

discrim settled into a thin engine shim after handing its model definitions to parsnip.

discrim is the parsnip extension for discriminant analysis, exposing linear, quadratic, flexible and regularized variants through the tidymodels interface. Its model definition functions moved into parsnip itself in 0.2.0, leaving this package as the engine and prediction layer. The two most recent releases are a documentation fix and a single prediction bug.

Read the full discrim 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 →

discrim vs insight: editorial side-by-side

D
discrim
ANALYTICS
0.0

discrim settled into a thin engine shim after handing its model definitions to parsnip.

◆ Current state

discrim is the parsnip extension for discriminant analysis, exposing linear, quadratic, flexible and regularized variants through the tidymodels interface. Its model definition functions moved into parsnip itself in 0.2.0, leaving this package as the engine and prediction layer. The two most recent releases are a documentation fix and a single prediction bug.

◆ Where it's heading

The package built out method coverage early, adding quadratic discriminant analysis in 0.1.2, the sda and sparsediscrim engines in 0.1.3 and case weights in 1.0.0, then stopped growing. Handing definitions upstream to parsnip in 0.2.0 confirmed the shape: discrim is where engines are wired, not where the API lives. Cadence since 2022 is roughly one small fix a year.

◆ Prediction

Nothing in the entries points to new methods or engines; the next release is most likely another CRAN or prediction-path fix.

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 discrim 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 discrim or insight.

See all discrim alternatives → · See all insight alternatives →

Recent activity from discrim 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. 8mo agodiscrimFix for FDA models failing at prediction time
  8. 11mo agodiscrimDocumentation links updated to stay on CRAN
  9. 4y agodiscrimCase weights enabled for flexible and linear discriminant models
  10. 4y agodiscrimModel definitions moved upstream into parsnip
  11. 5y agodiscrimsda and sparsediscrim engines added for LDA and QDA
  12. 5y agodiscrimdiscrim_quad() added; package relicensed to MIT

Frequently asked questions

What is the difference between discrim and insight?

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

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

Top discrim alternatives in Analytics are ranked by recent ship velocity. Browse the "discrim alternatives" section above for the current picks, or visit /alternatives/discrim 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.