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forecasting vs susier

A side-by-side editorial comparison of forecasting and susier — release velocity, themes, recent moves, and the top alternatives to consider.

forecasting vs susier: at a glance

Featureforecastingsusier
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, epidemiology, reproducibility, vignettesr-package, statistical-genetics, fine-mapping, cpp-bindings
Last editorial update3h ago48m ago
WebsiteVisit →Visit →

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.

Read the full forecasting trajectory →

What is susier?

Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs

susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.

Read the full susier trajectory →

forecasting vs susier: editorial side-by-side

F
forecasting
ANALYTICS
0.0

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.

S
susier
ANALYTICS
0.0

Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs

◆ Current state

susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.

◆ Where it's heading

The version-number churn understates how narrow this work is — four consecutive releases touching the same trimming and residual-variance machinery suggests one area where the implementation and the intended behavior had drifted apart. The 0.16.0 binding migration is the only structural change, and it is invisible to users while mattering for build portability and long-term maintenance. Development is clearly active, with automated release tooling and dependency bumps flowing through the same stream.

◆ Prediction

With the binding migration just landed, near-term releases are likely to address fallout from it alongside continued fixes in the same trimming and residual-variance code.

Alternatives to forecasting and susier

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 susier.

See all forecasting alternatives → · See all susier alternatives →

Recent activity from forecasting and susier

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoforecastingVignettes rebuilt under R 4.6.1
  2. 3mo agosusierMigrates C++ bindings from Rcpp to cpp11 and cpp11armadillo
  3. 3mo agosusierFixes alpha0/beta0 handling under Servin-Stephens
  4. 4mo agosusierCorrects the null space ELBO term for RSS with X
  5. 5mo agosusierFixes null effect trimming with non-uniform prior weights
  6. 5mo agosusierFixes null effect trimming under Servin-Stephens estimation
  7. 2y agoforecastingVignettes rebuilt under R 4.3.2
  8. 5y agoforecastingVignettes rebuilt under R 4.0.4
  9. 7y agoforecastingStandard PIT and discretized log-normal scoring
  10. 7y agoforecastingThe version used for the book chapter, with pinned dependencies

Frequently asked questions

What is the difference between forecasting and susier?

They serve adjacent needs but don't currently overlap on shipped themes. forecasting and susier 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 susier?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. forecasting and susier 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 susier?

Top susier alternatives in Analytics are ranked by recent ship velocity. Browse the "susier alternatives" section above for the current picks, or visit /alternatives/susier for the full list with editorial commentary on each.