randomwalk
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
A side-by-side editorial comparison of discretefdr and simStateSpace — release velocity, themes, recent moves, and the top alternatives to consider.
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.
State-space data simulation for R, filled in one function at a time
simStateSpace generates data from state-space models — discrete-time SSM and VAR, continuous-time linear SDE and Ornstein-Uhlenbeck — for use in simulation studies of longitudinal and intensive repeated-measures designs. Recent releases add moment and intercept helpers rather than new model families: SimMVN(), the LinSDE intercept functions, and consolidation of the four separate parameter-simulation functions into one. Release notes are terse, marked Patch, and typically name one or two functions.
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.
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.
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.
simStateSpace generates data from state-space models — discrete-time SSM and VAR, continuous-time linear SDE and Ornstein-Uhlenbeck — for use in simulation studies of longitudinal and intensive repeated-measures designs. Recent releases add moment and intercept helpers rather than new model families: SimMVN(), the LinSDE intercept functions, and consolidation of the four separate parameter-simulation functions into one. Release notes are terse, marked Patch, and typically name one or two functions.
The package is being filled in methodically toward completeness across its four model families — whatever exists for the SSM side eventually appears for LinSDE and back again, as SSMInterceptEta/SSMInterceptY in 1.2.15 were followed by their LinSDE counterparts in 1.2.16. The other visible move was outward: bootstrap components were split into a separate bootStateSpace package, keeping this one to simulation alone. It sits in the same author's cluster of state-space and mediation packages, whose published methods papers the releases cite.
Expect the pattern to continue — small patch releases adding the missing counterpart function for a model family already served, with any larger capability likely spun out into its own package as bootstrapping was.
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 simStateSpace.
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
See all discretefdr alternatives → · See all simStateSpace alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. discretefdr and simStateSpace 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discretefdr and simStateSpace 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.
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.
Top simStateSpace alternatives in Analytics are ranked by recent ship velocity. Browse the "simStateSpace alternatives" section above for the current picks, or visit /alternatives/simstatespace for the full list with editorial commentary on each.