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kde1d vs medrobust

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

kde1d vs medrobust: at a glance

Featurekde1dmedrobust
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdensity-estimation, kernel-methods, zero-inflation, cpp-librarycausal mediation, partial identification, misclassification, sensitivity analysis
Last editorial update1h ago8h ago
WebsiteVisit →Visit →

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 →

What is medrobust?

medrobust made its partial-identification bounds usable by giving them confidence intervals.

medrobust computes partial-identification bounds for mediation effects when exposure or mediator is differentially misclassified, part of the Data-Wise mediationverse. Its 0.2.0 release corrected three estimator defects against population oracles and added Imbens-Manski confidence intervals for the bounds; the two releases since have paired each identification path with a real public-domain dataset and a worked vignette. CRAN is deferred, with distribution through GitHub and r-universe.

Read the full medrobust trajectory →

kde1d vs medrobust: editorial side-by-side

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.

M
medrobust
ANALYTICS
0.0

medrobust made its partial-identification bounds usable by giving them confidence intervals.

◆ Current state

medrobust computes partial-identification bounds for mediation effects when exposure or mediator is differentially misclassified, part of the Data-Wise mediationverse. Its 0.2.0 release corrected three estimator defects against population oracles and added Imbens-Manski confidence intervals for the bounds; the two releases since have paired each identification path with a real public-domain dataset and a worked vignette. CRAN is deferred, with distribution through GitHub and r-universe.

◆ Where it's heading

The pattern is deliberate and symmetric: 0.3.0 shipped the mediator-side example on NCHS natality data, 0.4.0 its exposure-side mirror on NHANES, each demonstrating what the bounds do when reporting accuracy is allowed to depend on the outcome. Alongside that runs a consistent concern with failing usefully rather than loudly — bound_ne() returns NA bounds with a machine-readable reason and a typed condition instead of aborting, so a simulation replicate is recorded rather than lost, and non-finite endpoint standard errors produce a documented NA rather than a silent one. That is a package expecting to be run thousands of times inside someone else's loop.

◆ Prediction

Both identification paths now have a dataset, a vignette and interval coverage, so the next release is most likely the deferred CRAN submission rather than new methodology.

Alternatives to kde1d and medrobust

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 kde1d or medrobust.

See all kde1d alternatives → · See all medrobust alternatives →

Recent activity from kde1d and medrobust

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

  1. 2mo agomedrobustNHANES exposure-side misclassification example dataset
  2. 2mo agomedrobustNatality example dataset; bounds degrade instead of aborting
  3. 2mo agomedrobustBounds corrected against oracles; Imbens-Manski intervals added
  4. 1y agokde1dkde1d 1.1.1
  5. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  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 kde1d and medrobust?

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

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

What are the best alternatives to medrobust?

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