bootStateSpace
A parametric bootstrap for state-space models, shipped and then left alone.
A side-by-side editorial comparison of bagyo and forecasting — release velocity, themes, recent moves, and the top alternatives to consider.
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.
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
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.
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
The release pattern is maintenance on an eight-year cadence dictated entirely by the surrounding ecosystem: 1.1.1 rebuilt under R 4.0.4, 1.1.2 under R 4.3.2, 1.1.3 under R 4.6.1, each reporting whether the numbers moved. They mostly have not — the recurring note is minor numerical differences confined to the prophet forecasts in vignette('CHILI_prophet'). The only substantive change in the visible history is 1.1.0's methodological tidy-up of the scoring comparisons.
Nothing in these entries points to new functionality; the next release is most likely another vignette rebuild whenever a dependency change or a CRAN check failure forces one.
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 bagyo or forecasting.
A parametric bootstrap for state-space models, shipped and then left alone.
A Brazilian housing-data palette package went from internal tooling to public 1.0 in five days.
The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.
flashlight hit 1.0 by giving away its SHAP feature and making most of its API internal.
A palette generator became a palette platform — and changed the metric behind every color it picks.
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
See all bagyo alternatives → · See all forecasting alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — cran — within Analytics. bagyo and forecasting 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. bagyo and forecasting 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 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.
Top forecasting alternatives in Analytics are ranked by recent ship velocity. Browse the "forecasting alternatives" section above for the current picks, or visit /alternatives/forecasting for the full list with editorial commentary on each.