TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
A side-by-side editorial comparison of abclass and bagyo — release velocity, themes, recent moves, and the top alternatives to consider.
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
An implementation of multi-category angle-based large-margin classifiers with regularization. The capability was assembled in four releases across 2022: group lasso, then group SCAD and MCP penalties, then sparse matrix input, cross-validation via cv.abclass(), an efficient tuning path in et.abclass(), and experimental sup-norm classifiers. After a three-year gap, 0.5.0 simplified how group penalties are specified and 0.5.1 swapped the quadratic programming backend after qpmadr was archived on CRAN.
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
A data package distributing Philippine Area of Responsibility tropical cyclone records, developed through 2024 pre-releases and accepted by CRAN in early 2026. The substantive release is v0.2.0: 2021 and 2022 typhoon data added, an unexported helper for downloading cyclone reports, CITATION.cff, an R 4.1 dependency for the base pipe, and a full pass over vignettes, tests and README. The v0.1.1 tag announcing the first CRAN release carries no content and is stamped two hours after v0.2.0.
An implementation of multi-category angle-based large-margin classifiers with regularization. The capability was assembled in four releases across 2022: group lasso, then group SCAD and MCP penalties, then sparse matrix input, cross-validation via cv.abclass(), an efficient tuning path in et.abclass(), and experimental sup-norm classifiers. After a three-year gap, 0.5.0 simplified how group penalties are specified and 0.5.1 swapped the quadratic programming backend after qpmadr was archived on CRAN.
The methods surface is complete and the package has moved into maintenance, where releases are triggered by the R ecosystem rather than by research. The one structural habit worth noting is a willingness to change defaults — alpha, epsilon, lum_c and now the cross-validation alignment have all shifted between versions, so results are not stable across upgrades unless arguments are set explicitly.
Expect further releases to track CRAN dependency changes, as 0.5.1 did within a day of qpmadr's archival; nothing in the entries points to new penalty families.
A data package distributing Philippine Area of Responsibility tropical cyclone records, developed through 2024 pre-releases and accepted by CRAN in early 2026. The substantive release is v0.2.0: 2021 and 2022 typhoon data added, an unexported helper for downloading cyclone reports, CITATION.cff, an R 4.1 dependency for the base pipe, and a full pass over vignettes, tests and README. The v0.1.1 tag announcing the first CRAN release carries no content and is stamped two hours after v0.2.0.
The package is establishing itself as a citable, yearly-updated dataset rather than a one-off scrape — the download helper and the '2022 data and general yearly upkeep' commit both point at a recurring refresh, and the CRAN DOI and CITATION file exist so the data can be cited in papers. It sits alongside the same maintainer's other public-health and survey data packages, which received matching repository upkeep in the same month.
Expect an annual data release adding the next typhoon season, since that is the only recurring change in the history and the download helper was written to support it.
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 abclass or bagyo.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
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The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
See all abclass alternatives → · See all bagyo alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. abclass and bagyo 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. abclass and bagyo 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 abclass alternatives in Analytics are ranked by recent ship velocity. Browse the "abclass alternatives" section above for the current picks, or visit /alternatives/abclass for the full list with editorial commentary on each.
Top bagyo alternatives in Analytics are ranked by recent ship velocity. Browse the "bagyo alternatives" section above for the current picks, or visit /alternatives/bagyo for the full list with editorial commentary on each.