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feasts vs modelbased

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

feasts vs modelbased: at a glance

Featurefeastsmodelbased
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestime-series, r-stats, deprecation, package-spliteasystats, marginal-effects, contrasts, mixed-models
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is feasts?

feasts is splitting itself in two, moving every plot into ggtime

feasts provides feature extraction and statistics for tsibble time series. The last two releases are dominated by one decision: all of its gg_*() plotting functions are being moved out into a separate ggtime package. 0.4.2 announced the deprecation and 0.5.0 makes ggtime a dependency with soft-deprecation messages on every re-export.

Read the full feasts trajectory →

What is modelbased?

modelbased is turning marginal effects into a full contrast grammar

modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.

Read the full modelbased trajectory →

feasts vs modelbased: editorial side-by-side

F
feasts
ANALYTICS
0.0

feasts is splitting itself in two, moving every plot into ggtime

◆ Current state

feasts provides feature extraction and statistics for tsibble time series. The last two releases are dominated by one decision: all of its gg_*() plotting functions are being moved out into a separate ggtime package. 0.4.2 announced the deprecation and 0.5.0 makes ggtime a dependency with soft-deprecation messages on every re-export.

◆ Where it's heading

The package is narrowing to its stated purpose — features and statistics — and shedding graphics entirely over a deliberately slow two-year window. Everything else in the recent history is ggplot2 compatibility work and narrow seasonal-plot bug fixes, which is consistent with a maintainer trimming surface area rather than growing it.

◆ Prediction

The next releases should be compatibility upkeep while the ggtime deprecation runs its course; the re-exports stay until the announced window closes.

M
modelbased
ANALYTICS
0.0

modelbased is turning marginal effects into a full contrast grammar

◆ Current state

modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.

◆ Where it's heading

The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.

◆ Prediction

With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.

Alternatives to feasts and modelbased

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 feasts or modelbased.

See all feasts alternatives → · See all modelbased alternatives →

Recent activity from feasts and modelbased

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

  1. 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
  2. 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
  3. 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
  4. 6mo agofeastsfeasts moves its plots to ggtime behind a 2-year deprecation
  5. 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
  6. 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
  7. 11mo agofeastsggplot2 4.0.0 compatibility and the ggtime deprecation notice
  8. 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
  9. 1y agofeastsgg_season() fix for sub-weekly daily data
  10. 1y agofeastsImpulse-response plots and Johansen cointegration tests
  11. 2y agofeastsPatch for ggplot2 3.5.0 breaking changes
  12. 3y agofeastsCRAN patch for S3 method consistency

Frequently asked questions

What is the difference between feasts and modelbased?

They serve adjacent needs but don't currently overlap on shipped themes. feasts and modelbased 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 feasts better than modelbased?

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

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

What are the best alternatives to modelbased?

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