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kde1d vs labelled

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

Shared themes:r-package

kde1d vs labelled: at a glance

Featurekde1dlabelled
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdensity-estimation, kernel-methods, zero-inflation, cpp-librarysurvey-data, data-labels, stata-spss, metadata
Last editorial update1h ago2h 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 labelled?

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

Read the full labelled trajectory →

kde1d vs labelled: 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.

L
labelled
ANALYTICS
0.0

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

◆ Current state

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

◆ Where it's heading

The arc is toward being usable wherever labelled data ends up, not just where it is loaded. Each recent release either extends support to another object type — survey designs, packed columns, plain vectors, tibbles with list columns — or adds a conversion path between labels and some other representation. The look_for() search function has become a second centre of gravity alongside the label accessors, accumulating its own output formats and long-format conversions.

◆ Prediction

The pattern of adding compatibility with one more object type or output format per release is stable and likely continues. Nothing in these entries indicates a change to the underlying haven_labelled representation the package is built on.

Alternatives to kde1d and labelled

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 labelled.

See all kde1d alternatives → · See all labelled alternatives →

Recent activity from kde1d and labelled

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

  1. 9mo agolabelledFormatted look_for() tables and two-way dictionary conversion
  2. 11mo agolabelledSurvey design objects supported across the package
  3. 1y agokde1dkde1d 1.1.1
  4. 1y agolabelledRegression in set_variable_labels() corrected
  5. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  6. 1y agolabelledcli adopted for all messaging; null_action gains options
  7. 2y agolabelledCustom functions can rewrite variable and value labels in bulk
  8. 3y agolabelledPacked columns supported and label attributes exposed directly
  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 labelled?

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

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

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