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kde1d vs robma

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

Shared themes:r-package

kde1d vs robma: at a glance

Featurekde1drobma
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdensity-estimation, kernel-methods, zero-inflation, cpp-libraryr-package, meta-analysis, bayesian, api-redesign
Last editorial update48m ago4h 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 robma?

RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy

RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.

Read the full robma trajectory →

kde1d vs robma: 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.

R
robma
ANALYTICS
0.0

RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy

◆ Current state

RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.

◆ Where it's heading

The 3.x series solved the modeling problem and left an interface problem behind: a caller had to know which of six constructors matched their data type, and argument names differed across them. 4.0.0 resolves that by making the model family a set of arguments rather than a function name, and by standardizing input naming on metafor-style conventions. It shipped one day after BayesTools 0.3.0, the author's own upstream infrastructure package, whose new standardization and prior-transformation machinery this rewrite depends on.

◆ Prediction

A rewrite this wide usually needs a follow-up, so expect 4.0.x patches addressing migration gaps as users hit the removed constructors and renamed arguments.

Alternatives to kde1d and robma

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 robma.

See all kde1d alternatives → · See all robma alternatives →

Recent activity from kde1d and robma

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

  1. 3mo agorobmaUnifies six model constructors into one brma class hierarchy
  2. 8mo agorobmaRoBMA 3.6.1
  3. 11mo agorobmaRoBMA 3.6.0
  4. 1y agorobmaRoBMA 3.5.1
  5. 1y agokde1dkde1d 1.1.1
  6. 1y agorobmaRoBMA 3.5.0
  7. 1y agorobmaRoBMA 3.4.0
  8. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  9. 4y agokde1dBit-wise Boolean operations removed
  10. 5y agokde1ddkde1d() invisible output fixed
  11. 5y agokde1dValgrind false positive silenced
  12. 6y agokde1dqrng dependency dropped; undefined behaviour fixed

Frequently asked questions

What is the difference between kde1d and robma?

Both compete on the same themes — r-package — within Analytics. kde1d and robma 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 robma?

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

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