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Comparison · Analytics

fable vs forecast

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

Shared themes:forecastingtime-seriesr-statsmodel-classes

fable vs forecast: at a glance

Featurefableforecast
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, time-series, r-stats, model-classesforecasting, time-series, r-stats, major-release
Last editorial update5d ago5d ago
WebsiteVisit →Visit →

What is fable?

fable keeps widening its model shelf, one econometric class at a time

fable is the tidyverts forecasting engine, and its releases are almost entirely about which model families it can express. The 0.4.x line added the vector-error-correction and VARIMA classes plus impulse-response methods; 0.5.0 adds fractional differencing via ARFIMA. Between those, the releases are CRAN-check patches and documentation passes.

Read the full fable trajectory →

What is forecast?

After years of pure maintenance, forecast 9.0.0 reopens the package

forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.

Read the full forecast trajectory →

fable vs forecast: editorial side-by-side

F
fable
ANALYTICS
0.0

fable keeps widening its model shelf, one econometric class at a time

◆ Current state

fable is the tidyverts forecasting engine, and its releases are almost entirely about which model families it can express. The 0.4.x line added the vector-error-correction and VARIMA classes plus impulse-response methods; 0.5.0 adds fractional differencing via ARFIMA. Between those, the releases are CRAN-check patches and documentation passes.

◆ Where it's heading

The package is closing the gap with the older forecast package's model coverage while keeping the tidy model-specification grammar. Each substantive release is a new model class plus the generate()/IRF() plumbing to make it behave like the existing ones. Maintenance releases cluster around CRAN policy and ggplot2/tsibble compatibility rather than internal rewrites.

◆ Prediction

Expect the next substantive release to add another model class or extend generate()/IRF() coverage to the classes that still lack them, rather than change the modelling interface.

F
forecast
ANALYTICS
0.0

After years of pure maintenance, forecast 9.0.0 reopens the package

◆ Current state

forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.

◆ Where it's heading

The major version reframes forecast around explicit *_model() constructors — mean, random walk, spline, theta, Croston — rather than the older function-per-method style, and the 9.0.x patches since have been performance and argument-handling cleanups on top. That is an active maintenance line, not a package winding down in favour of fable.

◆ Prediction

Expect continued 9.0.x patches consolidating the new constructors and their forecast methods, with the older interfaces kept working alongside them.

Alternatives to fable and forecast

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 fable or forecast.

See all fable alternatives → · See all forecast alternatives →

Recent activity from fable and forecast

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

  1. 5mo agoforecastFixes for checkresiduals() and mstl() lambda handling
  2. 6mo agoforecastFaster ARFIMA search and forecast.mlm() argument handling
  3. 6mo agofablefable adds ARFIMA and fractional differencing
  4. 7mo agoforecastforecast 9.0.0 adds five model constructors and rewrites accuracy()
  5. 1y agoforecastDocumentation and bug-fix release
  6. 1y agofableIndexing and generate() fixes for VECM models
  7. 1y agofableVECM and VARIMA models land, plus IRF for VAR and ARIMA
  8. 2y agoforecastRNG state and base-R head/tail compatibility
  9. 2y agofablePatch for C++ R header changes
  10. 2y agoforecastMuch faster hfitted() for ARIMA and ETS models
  11. 2y agofableCRAN check patch with generate() fixes
  12. 3y agofableTSLM forecasts gain Student's t intervals

Frequently asked questions

What is the difference between fable and forecast?

Both compete on the same themes — forecasting, time-series, r-stats, model-classes — within Analytics. fable and forecast 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 fable better than forecast?

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

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

What are the best alternatives to forecast?

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