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collinear vs fillpattern

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

collinear vs fillpattern: at a glance

Featurecollinearfillpattern
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmulticollinearity, variable selection, vif, breaking changesggplot2, data-visualization, accessibility, graphics
Last editorial update5h 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 fillpattern?

Pattern fills for ggplot2, hardened against the ways users write sizes

fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.

Read the full fillpattern trajectory →

collinear vs fillpattern: 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.

F
fillpattern
ANALYTICS
0.0

Pattern fills for ggplot2, hardened against the ways users write sizes

◆ Current state

fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.

◆ Where it's heading

Development is slow and entirely reactive to how the string-based size interface fails. The pattern across releases is the same: a user hits an edge — very small fill areas in 1.0.2, malformed unit strings in 1.0.3 — and the fix is either a graceful fallback or a clearer error. Leaning on R's newer graphics engine rather than reimplementing pattern rendering keeps the package small at the cost of raising its version floor.

◆ Prediction

Expect further releases to stay in the same register: parsing and validation fixes for the size and unit interface, with the pattern set itself unlikely to change.

Alternatives to collinear and fillpattern

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 fillpattern.

See all collinear alternatives → · See all fillpattern alternatives →

Recent activity from collinear and fillpattern

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

  1. 3mo agocollinearNamespace, NA and sf fixes; example data moves to spatialData
  2. 6mo agofillpatternSize string parsing fixed; invalid units now report instead of crash
  3. 8mo agocollinearAdaptive thresholds, multi-response support and a new output class
  4. 1y agocollinearCategorical responses, f_auto() defaults and future-based parallelism
  5. 2y agofillpatternSmall fill areas no longer crash; min_size falls back to solid
  6. 2y agofillpatternfillpattern 1.0.1

Frequently asked questions

What is the difference between collinear and fillpattern?

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

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

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