treasury
A thin Treasury rates wrapper has stopped adding endpoints and started making its tables self-describing.
Comparison · Analytics
forecasting vs hydroloom
A side-by-side editorial comparison of forecasting and hydroloom — release velocity, themes, recent moves, and the top alternatives to consider.
forecasting vs hydroloom: at a glance
What is forecasting?
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.
What is hydroloom?
USGS puts a type system over its river network toolkit so errors surface at dispatch
hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.
forecasting vs hydroloom: editorial side-by-side
forecasting
0.0ANALYTICS
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
hydroloom
0.0ANALYTICS
USGS puts a type system over its river network toolkit so errors surface at dispatch
◆ Current state
hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.
◆ Where it's heading
The package spent its first releases porting and broadening — non-dendritic network support, divergence routing, subsetting that follows diversions out of a basin — and has now turned to making that surface safe to use. The class hierarchy is the structural expression of that turn: instead of every function re-checking whether a data frame has the columns it needs, the type carries the guarantee. The explicit outlet rule resolves a category of failure where valid networks errored on NA or orphan toid values.
◆ Prediction
The release notes flag that subclass attributes are stripped by standard dplyr operations, which is the kind of rough edge that usually generates follow-up work — expect attribute preservation or restoration helpers next.
Alternatives to forecasting and hydroloom
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 forecasting or hydroloom.
soilDB
The R front door to USDA soil data finishes a long deprecation cleanup and turns local-first.
lstar
A single-cell data store commits to Zarr v3 and range-readable hosting across four language surfaces
quanteda
Text analysis in R keeps optimising its token internals — and builds a path out to torch
moderndive
The ModernDive teaching package learns to render inside the browser that runs its own textbook
glmbayes
A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain
See all forecasting alternatives → · See all hydroloom alternatives →
Recent activity from forecasting and hydroloom
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoforecastingVignettes rebuilt under R 4.6.1
- 2mo agohydroloomhydroloom v1.2.0 ⚡
- 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
- 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
- 10mo agohydroloomSort and indexing fixes
- 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
- 2y agoforecastingVignettes rebuilt under R 4.3.2
- 2y agohydroloomInitial release completing the nhdplusTools migration
- 5y agoforecastingVignettes rebuilt under R 4.0.4
- 7y agoforecastingStandard PIT and discretized log-normal scoring
- 7y agoforecastingThe version used for the book chapter, with pinned dependencies
Frequently asked questions
What is the difference between forecasting and hydroloom?
They serve adjacent needs but don't currently overlap on shipped themes. forecasting and hydroloom 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 forecasting better than hydroloom?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. forecasting and hydroloom 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 forecasting?
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.
What are the best alternatives to hydroloom?
Top hydroloom alternatives in Analytics are ranked by recent ship velocity. Browse the "hydroloom alternatives" section above for the current picks, or visit /alternatives/hydroloom for the full list with editorial commentary on each.