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discrim vs parameters

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

discrim vs parameters: at a glance

Featurediscrimparameters
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestidymodels, discriminant analysis, parsnip extension, classificationeasystats, model-parameters, standardization, mixed-models
Last editorial update4h ago1h 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 parameters?

easystats' parameters package absorbs one more model class every few weeks

parameters extracts and formats coefficients from an enormous range of R model objects, and its releases read as a running ledger of that range expanding — lavaan and lavaan.mi, survey, lcmm, glmmTMB, fixest, marginaleffects, ordinal. Recent versions ship roughly monthly with a mix of new support, new arguments, and fixes for label handling and standard errors. The most consequential recent change is behavioral: post-hoc standardization no longer standardizes the intercept, setting it and its inferential statistics to NA.

Read the full parameters trajectory →

discrim vs parameters: 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.

P
parameters
ANALYTICS
0.0

easystats' parameters package absorbs one more model class every few weeks

◆ Current state

parameters extracts and formats coefficients from an enormous range of R model objects, and its releases read as a running ledger of that range expanding — lavaan and lavaan.mi, survey, lcmm, glmmTMB, fixest, marginaleffects, ordinal. Recent versions ship roughly monthly with a mix of new support, new arguments, and fixes for label handling and standard errors. The most consequential recent change is behavioral: post-hoc standardization no longer standardizes the intercept, setting it and its inferential statistics to NA.

◆ Where it's heading

The package's job is to be the universal adapter for model output, so its roadmap is effectively set by what the R modelling ecosystem produces. Two threads are visible beyond coverage: getting standard errors right for awkward cases such as frailty terms and robust vcov matrices, and getting labels right when factors are converted on the fly or character variables appear in a formula. Interoperability inside easystats keeps tightening, with equivalence_test() gaining methods for modelbased objects.

◆ Prediction

Given the cadence, the next release will most likely add another model class alongside label and standard-error fixes rather than change how the package works.

Alternatives to discrim and parameters

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 parameters.

See all discrim alternatives → · See all parameters alternatives →

Recent activity from discrim and parameters

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

  1. 1mo agoparametersparameters 0.29.2 extends lavaan support and fixes label dropping
  2. 2mo agoparametersparameters 0.29.1 adds a cluster argument and fixes vcov handling
  3. 3mo agoparametersparameters 0.29.0 stops standardizing the intercept in post-hoc methods
  4. 8mo agodiscrimFix for FDA models failing at prediction time
  5. 8mo agoparametersparameters 0.28.3 adds Kenward-Roger and Satterthwaite for glmmTMB
  6. 11mo agoparametersparameters 0.28.2 updates tests for the latest fixest release
  7. 11mo agoparametersparameters 0.28.1 adds robust standard errors for glmmTMB
  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 parameters?

They serve adjacent needs but don't currently overlap on shipped themes. discrim and parameters 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 parameters?

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

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