PurpleAir
The R client for PurpleAir sensors keeps finding its time-averaging was wrong.
A side-by-side editorial comparison of b3gbi and discretefdr — release velocity, themes, recent moves, and the top alternatives to consider.
b3gbi pulled confidence intervals out of its indicator workflow and handed them to dubicube.
b3gbi computes biodiversity indicators from GBIF occurrence cubes for the B-Cubed project, and sits at 0.9.4 in a JOSS review run-up. The 0.9 release decoupled uncertainty from indicator calculation: confidence intervals are no longer produced inline but added afterward with add_ci(), backed by whole-cube bootstrapping from the sibling dubicube package. Everything since has been grid-parsing and compatibility repair around that split.
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.
b3gbi computes biodiversity indicators from GBIF occurrence cubes for the B-Cubed project, and sits at 0.9.4 in a JOSS review run-up. The 0.9 release decoupled uncertainty from indicator calculation: confidence intervals are no longer produced inline but added afterward with add_ci(), backed by whole-cube bootstrapping from the sibling dubicube package. Everything since has been grid-parsing and compatibility repair around that split.
Two forces are shaping releases. Internally, the uncertainty split produced an indicator-specific rule book — species-level indicators bootstrap the whole cube, raw counts resample within year, evenness gets a logit transform — and that rule book is where the statistical thinking now lives. Externally, GBIF's taxonomic backbone migration to the Catalogue of Life forced string taxon keys through process_cube() and the plotting paths, while recurring EEA and MGRS grid-code fixes mark coordinate parsing as the least settled area.
The 0.9.4 notes are entirely JOSS review items — contributors, examples, tracked datasets — so the next release is most likely a JOSS-accepted 1.0 rather than new indicator work.
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.
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 b3gbi or discretefdr.
The R client for PurpleAir sensors keeps finding its time-averaging was wrong.
A board game graphics package runs one of the most disciplined deprecation cycles in R.
The explainable-ensemble-tree package now measures whether its own explanations are faithful.
A scientific-text analysis package moved from counting citations to classifying argument structure.
The teaching arm of an R reliability suite keeps pace with whatever its analysis siblings ship.
The Weibull plotting package renamed itself, then handed its charts to AI assistants.
See all b3gbi alternatives → · See all discretefdr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. b3gbi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. b3gbi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top b3gbi alternatives in Analytics are ranked by recent ship velocity. Browse the "b3gbi alternatives" section above for the current picks, or visit /alternatives/b3gbi for the full list with editorial commentary on each.
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.