← Back to home
Comparison · Analytics

effectplots vs kde1d

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

Shared themes:r-package

effectplots vs kde1d: at a glance

Featureeffectplotskde1d
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, model-interpretability, ale, partial-dependencedensity-estimation, kernel-methods, zero-inflation, cpp-library
Last editorial update49m ago1h ago
WebsiteVisit →Visit →

What is effectplots?

A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.

effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.

Read the full effectplots 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 →

effectplots vs kde1d: editorial side-by-side

E
effectplots
ANALYTICS
0.0

A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.

◆ Current state

effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.

◆ Where it's heading

After 0.2.0 the work turns to the awkward cases - missing values on the x axis, explicit and empty factor levels, discrete grid detection. The package is also widening past a single modelling ecosystem: h2o support and tidymodels examples arrived with 0.2.0, and fcut() was exported as a fast replacement for cut(). Release notes are issue-numbered throughout, so the roadmap is effectively the issue tracker.

◆ Prediction

Expect continued default tuning around collapse_m and discrete_m plus more model-backend coverage; the cadence points to another batch of issue fixes rather than a new plot type.

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 effectplots 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 effectplots or kde1d.

See all effectplots alternatives → · See all kde1d alternatives →

Recent activity from effectplots and kde1d

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

  1. 1y agokde1dkde1d 1.1.1
  2. 1y agoeffectplotsRare categories collapse into an 'other' level
  3. 1y agoeffectplotsMissing x values now plotted for numeric features
  4. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  5. 1y agoeffectplotsNumeric core rewritten after an in-place data corruption fix
  6. 1y agoeffectplotsInitial CRAN release
  7. 4y agokde1dBit-wise Boolean operations removed
  8. 5y agokde1ddkde1d() invisible output fixed
  9. 5y agokde1dValgrind false positive silenced
  10. 6y agokde1dqrng dependency dropped; undefined behaviour fixed

Frequently asked questions

What is the difference between effectplots and kde1d?

Both compete on the same themes — r-package — within Analytics. effectplots 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 effectplots better than kde1d?

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

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