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collinear vs kde1d

A side-by-side editorial comparison of collinear and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.

collinear vs kde1d: at a glance

Featurecollinearkde1d
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmulticollinearity, variable selection, vif, breaking changesdensity-estimation, kernel-methods, zero-inflation, cpp-library
Last editorial update8h 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 kde1d?

A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.

kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.

Read the full kde1d trajectory →

collinear vs kde1d: 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.

K
kde1d
ANALYTICS
0.0

A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.

◆ Current state

kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.

◆ Where it's heading

The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.

◆ Prediction

With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.

Alternatives to collinear and kde1d

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 kde1d.

See all collinear alternatives → · See all kde1d alternatives →

Recent activity from collinear and kde1d

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

  1. 3mo agocollinearNamespace, NA and sf fixes; example data moves to spatialData
  2. 8mo agocollinearAdaptive thresholds, multi-response support and a new output class
  3. 1y agokde1dkde1d 1.1.1
  4. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  5. 1y agocollinearCategorical responses, f_auto() defaults and future-based parallelism
  6. 4y agokde1dBit-wise Boolean operations removed
  7. 5y agokde1ddkde1d() invisible output fixed
  8. 5y agokde1dValgrind false positive silenced
  9. 6y agokde1dqrng dependency dropped; undefined behaviour fixed

Frequently asked questions

What is the difference between collinear and kde1d?

They serve adjacent needs but don't currently overlap on shipped themes. collinear and kde1d 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 kde1d?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collinear and kde1d 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 kde1d?

Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.