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forecasting vs labelled

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

forecasting vs labelled: at a glance

Featureforecastinglabelled
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, epidemiology, reproducibility, vignettessurvey-data, data-labels, stata-spss, metadata
Last editorial update6h ago46m 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 labelled?

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

Read the full labelled trajectory →

forecasting vs labelled: 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.

L
labelled
ANALYTICS
0.0

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

◆ Current state

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

◆ Where it's heading

The arc is toward being usable wherever labelled data ends up, not just where it is loaded. Each recent release either extends support to another object type — survey designs, packed columns, plain vectors, tibbles with list columns — or adds a conversion path between labels and some other representation. The look_for() search function has become a second centre of gravity alongside the label accessors, accumulating its own output formats and long-format conversions.

◆ Prediction

The pattern of adding compatibility with one more object type or output format per release is stable and likely continues. Nothing in these entries indicates a change to the underlying haven_labelled representation the package is built on.

Alternatives to forecasting and labelled

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 labelled.

See all forecasting alternatives → · See all labelled alternatives →

Recent activity from forecasting and labelled

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

  1. 1mo agoforecastingVignettes rebuilt under R 4.6.1
  2. 9mo agolabelledFormatted look_for() tables and two-way dictionary conversion
  3. 11mo agolabelledSurvey design objects supported across the package
  4. 1y agolabelledRegression in set_variable_labels() corrected
  5. 1y agolabelledcli adopted for all messaging; null_action gains options
  6. 2y agolabelledCustom functions can rewrite variable and value labels in bulk
  7. 2y agoforecastingVignettes rebuilt under R 4.3.2
  8. 3y agolabelledPacked columns supported and label attributes exposed directly
  9. 5y agoforecastingVignettes rebuilt under R 4.0.4
  10. 7y agoforecastingStandard PIT and discretized log-normal scoring
  11. 7y agoforecastingThe version used for the book chapter, with pinned dependencies

Frequently asked questions

What is the difference between forecasting and labelled?

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

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

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