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Comparison · Analytics

fabletools vs waywiser

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

Shared themes:r-package

fabletools vs waywiser: at a glance

Featurefabletoolswaywiser
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, tidyverts, model-combination, reconciliationspatial-statistics, model-assessment, tidymodels, cran-compliance
Last editorial update57m ago1h ago
WebsiteVisit →Visit →

What is fabletools?

The tidyverts forecasting core rebuilt model combination on full residual covariance.

fabletools is the framework layer under fable and fpp3 — mables, fables, accuracy measures, reconciliation, and the model arithmetic that lets forecasters express ensembles as expressions. Version 0.8.0 reworked that arithmetic: combination now uses a joint N-way convolution accounting for the full residual covariance across components rather than composing pairwise, and every arithmetic operator collapses to a single model_combination with correctly implied weights, so nested expressions like ((m1 + m2)/2 + m3)/2 flatten automatically. In parallel, the package has been shedding graphics to {ggtime} on a deliberately slow deprecation clock.

Read the full fabletools trajectory →

What is waywiser?

Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.

waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.

Read the full waywiser trajectory →

fabletools vs waywiser: editorial side-by-side

F
fabletools
ANALYTICS
0.0

The tidyverts forecasting core rebuilt model combination on full residual covariance.

◆ Current state

fabletools is the framework layer under fable and fpp3 — mables, fables, accuracy measures, reconciliation, and the model arithmetic that lets forecasters express ensembles as expressions. Version 0.8.0 reworked that arithmetic: combination now uses a joint N-way convolution accounting for the full residual covariance across components rather than composing pairwise, and every arithmetic operator collapses to a single model_combination with correctly implied weights, so nested expressions like ((m1 + m2)/2 + m3)/2 flatten automatically. In parallel, the package has been shedding graphics to {ggtime} on a deliberately slow deprecation clock.

◆ Where it's heading

The framework is being narrowed and deepened at the same time. Narrowed, because plotting is moving out to a dedicated package over an announced two-year deprecation, leaving fabletools to modeling infrastructure. Deepened, because the recent statistical work targets correctness in places users could not easily inspect — combination weights, inverse-variance weighting computed on response rather than innovation residuals, reconciliation coherency matrices exposed via coherent_smat() and coherent_cmat(). Class hygiene follows the same instinct, with mdl_lst replacing lst_mdl and gaining augment(), glance(), and tidy() so global and reconciliation models report statistics like any other.

◆ Prediction

With combination and reconciliation infrastructure freshly reworked, the remaining announced work is the ggtime separation, so expect the graphics re-exports to keep degrading toward removal while modeling changes stay incremental.

W
waywiser
ANALYTICS
0.0

Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.

◆ Current state

waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.

◆ Where it's heading

The package has reached the point where the interesting bugs are cross-platform and cross-package rather than statistical. Its main function, ww_multi_scale(), has been the focus of nearly every release since 0.4.0, working through units handling, aggregation ordering, raster inputs and metric-type dispatch. The dependency on vip and the tidymodels metric machinery means a share of releases exist only to track breaking changes elsewhere.

◆ Prediction

Expect the next substantive release to continue on ww_multi_scale() edge cases, given that it has absorbed most of the fixes in this window. The recent run of CRAN-compliance patches suggests no feature work is currently in flight.

Alternatives to fabletools and waywiser

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 fabletools or waywiser.

See all fabletools alternatives → · See all waywiser alternatives →

Recent activity from fabletools and waywiser

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

  1. 1mo agofabletoolsModel combination rebuilt on joint N-way convolution
  2. 3mo agofabletoolsCoherency matrices exposed, mdl_lst gains tidier methods
  3. 5mo agofabletoolsGraphics methods now require fabletools to be attached
  4. 6mo agofabletoolsTime series graphics migrating out to ggtime
  5. 8mo agofabletoolsggplot2 4.0.0 compatibility patch
  6. 8mo agofabletoolsIRF() generic and multivariate bootstrap sample paths
  7. 1y agowaywiserStops downloading data during CRAN checks
  8. 1y agowaywiserVignettes no longer write to CRAN directories
  9. 1y agowaywiserKeeps the R version floor below 4.1
  10. 2y agowaywiserNaN results become NA; raster metrics dispatch correctly
  11. 2y agowaywiserGuards against ignored grid arguments; faster on sf data
  12. 2y agowaywiserFixes wrong observation counts and ignored grid units

Frequently asked questions

What is the difference between fabletools and waywiser?

Both compete on the same themes — r-package — within Analytics. fabletools and waywiser 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 fabletools better than waywiser?

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

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

What are the best alternatives to waywiser?

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