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collinear vs discretefdr

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

collinear vs discretefdr: at a glance

Featurecollineardiscretefdr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmulticollinearity, variable selection, vif, breaking changesmultiple-testing, false-discovery-rate, discrete-statistics, r-package
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is collinear?

collinear has broken its API twice to stop making the user pick thresholds.

collinear removes multicollinearity from predictor sets through pairwise correlation and VIF filtering, with a preference order deciding which variable survives each conflict. Two major versions in thirteen months each rewrote the interface: 2.0.0 extended every function to any combination of categorical and numeric responses and predictors, and 3.0.0 moved to multiple responses, restructured the output into classed objects, and made both filtering thresholds adaptive by default. Version 3.0.1 is the first release since that is purely repair.

Read the full collinear trajectory →

What is discretefdr?

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

Read the full discretefdr trajectory →

collinear vs discretefdr: editorial side-by-side

C
collinear
ANALYTICS
0.0

collinear has broken its API twice to stop making the user pick thresholds.

◆ Current state

collinear removes multicollinearity from predictor sets through pairwise correlation and VIF filtering, with a preference order deciding which variable survives each conflict. Two major versions in thirteen months each rewrote the interface: 2.0.0 extended every function to any combination of categorical and numeric responses and predictors, and 3.0.0 moved to multiple responses, restructured the output into classed objects, and made both filtering thresholds adaptive by default. Version 3.0.1 is the first release since that is purely repair.

◆ Where it's heading

The through-line is removing decisions the user was never well placed to make. Preference-order functions were renamed twice — first onto a metric-and-model scheme in 2.0.0, then onto a response-type scheme in 3.0.0 — and f_auto() picks one when none is given; target encoding went from automatic to opt-in; max_cor and max_vif now default to NULL and trigger a data-driven threshold derived from the 75th percentile of pairwise correlations through a sigmoid and a fitted correlation-to-VIF mapping. Each change is defensible and each one broke callers, which is the cost of this approach.

◆ Prediction

3.0.1 moved the example datasets out into a separate spatialData package and fixed four crashes rather than adding anything, so the next release is most likely more consolidation on the 3.0 surface than a fourth interface.

D
discretefdr
ANALYTICS
0.0

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

◆ Current state

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

◆ Where it's heading

The direction is decomposition into a suite. The amnesia dataset went to DiscreteDatasets, summary output now interoperates with the DiscreteTestResults class from DiscreteTests, and match.pvals() stopped being exported — each release trims something that belongs elsewhere. What remains gets methodological additions at a slow, deliberate cadence, with performance work on the step-up procedures that dominate cost when the number of tests is large. Recent activity is maintenance: replacing deprecated calls the package still made of its own siblings. This is a mature statistical package whose release notes are short because the methods underneath them are settled.

◆ Prediction

Expect further alignment with the companion packages rather than new procedures, since the last substantive release was already about interoperating with DiscreteTests classes and the most recent one about clearing deprecations.

Alternatives to collinear and discretefdr

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 collinear or discretefdr.

See all collinear alternatives → · See all discretefdr alternatives →

Recent activity from collinear and discretefdr

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

  1. 3mo agodiscretefdrDeprecated internal calls replaced
  2. 3mo agocollinearNamespace, NA and sf fixes; example data moves to spatialData
  3. 8mo agocollinearAdaptive thresholds, multi-response support and a new output class
  4. 1y agodiscretefdrDiscrete Benjamini-Yekutieli procedure added
  5. 1y agocollinearCategorical responses, f_auto() defaults and future-based parallelism
  6. 1y agodiscretefdrDatasets split out and step-up procedures sped up

Frequently asked questions

What is the difference between collinear and discretefdr?

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

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

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

What are the best alternatives to discretefdr?

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