simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
discretefdr vs kde1d
A side-by-side editorial comparison of discretefdr and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
discretefdr vs kde1d: at a glance
What is discretefdr?
The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.
DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.
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.
discretefdr vs kde1d: editorial side-by-side
discretefdr
0.0ANALYTICS
The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.
◆ Current state
DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.
◆ Where it's heading
The direction is decomposition into a suite. The amnesia dataset went to DiscreteDatasets, summary output now interoperates with the DiscreteTestResults class from DiscreteTests, and match.pvals() stopped being exported — each release trims something that belongs elsewhere. What remains gets methodological additions at a slow, deliberate cadence, with performance work on the step-up procedures that dominate cost when the number of tests is large. Recent activity is maintenance: replacing deprecated calls the package still made of its own siblings. This is a mature statistical package whose release notes are short because the methods underneath them are settled.
◆ Prediction
Expect further alignment with the companion packages rather than new procedures, since the last substantive release was already about interoperating with DiscreteTests classes and the most recent one about clearing deprecations.
kde1d
0.0ANALYTICS
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 discretefdr 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 discretefdr or kde1d.
lavaanExtra
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
ibis.iSDM
A raster-to-terra migration is the only readable change in a feed of merge notes.
anyflights
A nycflights13 generator whose recent work is all about the data being right.
vinereg
Conditional density and log-likelihood fill out a vine copula regression package.
stringx
A drop-in string API for base R, kept alive by upstream check failures.
See all discretefdr alternatives → · See all kde1d alternatives →
Recent activity from discretefdr and kde1d
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agodiscretefdrDeprecated internal calls replaced
- 1y agokde1dkde1d 1.1.1
- 1y agodiscretefdrDiscrete Benjamini-Yekutieli procedure added
- 1y agokde1dZero-inflated mixtures and a new standalone C++ API ⚡
- 1y agodiscretefdrDatasets split out and step-up procedures sped up
- 4y agokde1dBit-wise Boolean operations removed
- 5y agokde1ddkde1d() invisible output fixed
- 5y agokde1dValgrind false positive silenced
- 6y agokde1dqrng dependency dropped; undefined behaviour fixed
Frequently asked questions
What is the difference between discretefdr and kde1d?
Both compete on the same themes — r-package — within Analytics. discretefdr 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 discretefdr better than kde1d?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discretefdr 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 discretefdr?
Top discretefdr alternatives in Analytics are ranked by recent ship velocity. Browse the "discretefdr alternatives" section above for the current picks, or visit /alternatives/discretefdr 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.