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modelbased vs timetk

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

Shared themes:r-package

modelbased vs timetk: at a glance

Featuremodelbasedtimetk
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeseasystats, marginal-effects, contrasts, mixed-modelstime-series, anomaly-detection, visualization, feature-engineering
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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 →

What is timetk?

timetk swallowed anomalize whole, then went quiet for two years

timetk handles time series wrangling, visualization, and feature engineering in a tidyverse idiom. Its defining recent move was absorbing the anomalize package outright in 2.9.0, bringing anomaly detection, cleaning, and the associated plots inside timetk rather than leaving them in a sibling package. Development then paused for nearly two years before 2.9.1, a robustness and documentation release.

Read the full timetk trajectory →

modelbased vs timetk: editorial side-by-side

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.

T
timetk
ANALYTICS
0.0

timetk swallowed anomalize whole, then went quiet for two years

◆ Current state

timetk handles time series wrangling, visualization, and feature engineering in a tidyverse idiom. Its defining recent move was absorbing the anomalize package outright in 2.9.0, bringing anomaly detection, cleaning, and the associated plots inside timetk rather than leaving them in a sibling package. Development then paused for nearly two years before 2.9.1, a robustness and documentation release.

◆ Where it's heading

The trajectory before the pause was consolidation: fold in adjacent functionality, then make the visualization layer handle many series at once via trelliscopejs, then broaden feature generation with tk_tsfeatures(). The recent release works on the least glamorous layer — internal generics so date parsing and sequence generation behave consistently across Date, POSIXct, hms, yearmon, and yearqtr — which is the kind of foundation work a package does when it has accumulated too many special cases. The long gap and the CI-refresh content suggest maintenance attention rather than a new direction.

◆ Prediction

The stated gap is the unimplemented twitter method for anomalize(), which is the one concrete outstanding item the release notes name; beyond that the recent work points to consolidation rather than expansion.

Alternatives to modelbased and timetk

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 modelbased or timetk.

See all modelbased alternatives → · See all timetk alternatives →

Recent activity from modelbased and timetk

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. 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
  5. 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
  6. 11mo agotimetktimetk 2.9.1 makes date parsing consistent across time classes
  7. 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
  8. 2y agotimetktimetk 2.9.0 absorbs the anomalize package
  9. 4y agotimetktimetk 2.8.1 exposes trelliscope plotting parameters
  10. 4y agotimetktimetk 2.8.0 adds trelliscopejs support for many-series plots
  11. 4y agotimetktimetk 2.7.0 adds tk_tsfeatures() for grouped feature matrices
  12. 4y agotimetktimetk 2.6.2 adds .week_start and facet direction controls

Frequently asked questions

What is the difference between modelbased and timetk?

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

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

What are the best alternatives to timetk?

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