bootStateSpace
A parametric bootstrap for state-space models, shipped and then left alone.
Comparison · Analytics
abclass vs forecasting
A side-by-side editorial comparison of abclass and forecasting — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r package
abclass vs forecasting: at a glance
What is abclass?
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.
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.
abclass vs forecasting: editorial side-by-side
abclass
0.0ANALYTICS
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
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.
Alternatives to abclass and forecasting
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 forecasting.
benviplot
A Brazilian housing-data palette package went from internal tooling to public 1.0 in five days.
labelled
The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.
flashlight
flashlight hit 1.0 by giving away its SHAP feature and making most of its API internal.
qualpalr
A palette generator became a palette platform — and changed the metric behind every color it picks.
mev
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
See all abclass alternatives → · See all forecasting alternatives →
Recent activity from abclass and forecasting
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoforecastingVignettes rebuilt under R 4.6.1
- 7mo agoabclassQuadratic programming backend swapped after CRAN archival
- 10mo agoabclassGroup penalty specification simplified
- 2y agoforecastingVignettes rebuilt under R 4.3.2
- 3y agoabclassSparse input, cross-validation and efficient tuning added
- 4y agoabclassGroup SCAD and MCP penalties added
- 4y agoabclassGroup lasso regularization and correctness fixes
- 4y agoabclassFirst release of the angle-based classifiers
- 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 abclass and forecasting?
Both compete on the same themes — r package — within Analytics. abclass 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.
Is abclass better than forecasting?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. abclass 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.
What are the best alternatives to abclass?
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.
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.