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gratia vs vim

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

Shared themes:r-package

gratia vs vim: at a glance

Featuregratiavim
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesgam, mgcv, ggplot2, statistical-graphicsr-package, missing-data, imputation, correctness-audit
Last editorial update45m ago4h ago
WebsiteVisit →Visit →

What is gratia?

The tidy front-end for GAMs, now stable enough that upstream ggplot2 sets its release calendar.

gratia wraps mgcv-fitted generalized additive models in tidy data frames and ggplot2 graphics — smooth_estimates(), fitted_values(), derivatives(), draw() and appraise() cover evaluation, prediction and diagnostics. The API reached its intended shape at 0.9.0, when every generated column was renamed to a dot-prefixed form, and 0.10.0 added conditional_values() for covariate-conditional prediction plots.

Read the full gratia trajectory →

What is vim?

Six dormant years end with a correctness audit across VIM's entire imputation surface

VIM handles visualization and imputation of missing values in R, with kNN, hot-deck, iterative robust model-based imputation and matching-based methods. Development effectively stopped after 6.0.0 in 2020. Version 7.2.0 arrives in July 2026 as an explicitly framed correctness milestone: MI-properness warnings, ordered-factor preservation, a keep_all_columns option, list returns from irmi(mi>1), repairs to imputeRobust and imputeRobustChain, cellwise IRWLS and initial-weight fixes, and kNN and gowerD mixed-scaling corrections with a weightDist guard.

Read the full vim trajectory →

gratia vs vim: editorial side-by-side

G
gratia
ANALYTICS
0.0

The tidy front-end for GAMs, now stable enough that upstream ggplot2 sets its release calendar.

◆ Current state

gratia wraps mgcv-fitted generalized additive models in tidy data frames and ggplot2 graphics — smooth_estimates(), fitted_values(), derivatives(), draw() and appraise() cover evaluation, prediction and diagnostics. The API reached its intended shape at 0.9.0, when every generated column was renamed to a dot-prefixed form, and 0.10.0 added conditional_values() for covariate-conditional prediction plots.

◆ Where it's heading

The package has moved through a long rewrite cycle and out the other side. Successive releases replaced evaluate_smooth() with smooth_estimates(), rebuilt draw() on top of it, then renamed the entire output vocabulary to avoid colliding with user variables. That work is finished; 0.11.1 is driven almost entirely by ggplot2 4.0.0 compatibility, with new mgcv family support for quantile residuals riding along. Development now tracks upstream breakage rather than internal redesign.

◆ Prediction

Expect the next releases to continue absorbing ggplot2 4.x and mgcv changes, with incremental family coverage in quantile_residuals() as the visible new work. The entries give no signal on which mgcv families come next.

V
vim
ANALYTICS
0.0

Six dormant years end with a correctness audit across VIM's entire imputation surface

◆ Current state

VIM handles visualization and imputation of missing values in R, with kNN, hot-deck, iterative robust model-based imputation and matching-based methods. Development effectively stopped after 6.0.0 in 2020. Version 7.2.0 arrives in July 2026 as an explicitly framed correctness milestone: MI-properness warnings, ordered-factor preservation, a keep_all_columns option, list returns from irmi(mi>1), repairs to imputeRobust and imputeRobustChain, cellwise IRWLS and initial-weight fixes, and kNN and gowerD mixed-scaling corrections with a weightDist guard.

◆ Where it's heading

The release notes describe an audit — Wave 1 plus tail — rather than a feature cycle, and the fixes cluster around statistical validity: whether multiple imputation is proper, whether factor ordering survives, whether distance scaling across mixed variable types is right. Those are the properties users cannot easily verify themselves, so a package correcting them after six years is implicitly restating what its earlier output was worth. The notes also name a forthcoming R Journal paper under the name vimpute, which points at a successor or companion identity.

◆ Prediction

The entries call this a stable reference point for a paper and refer to Wave 1, so a further audit wave is the most likely next release; the vimpute naming is worth watching but the entries do not say what it is.

Alternatives to gratia and vim

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 gratia or vim.

See all gratia alternatives → · See all vim alternatives →

Recent activity from gratia and vim

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

  1. 1mo agovimCorrectness audit fixes MI-properness, factor order and distance scaling
  2. 11mo agogratiaggplot2 4.0.0 compatibility, plus four more quantile-residual families
  3. 1y agogratiaconditional_values() replaces vis.gam for conditional prediction plots
  4. 2y agogratiaparametric_effects() joins the dot-prefix rename; LSS families begin
  5. 2y agogratiaEvery generated column gains a dot prefix
  6. 3y agogratiaReal variable names in smooth_samples(), plus dplyr 1.1.0 fixes
  7. 4y agogratiaM1 example output fixes and confint tibble returns
  8. 6y agovimAdds ranger-based imputation, drops survey and GUI support
  9. 6y agovimAdds nine example datasets and splits help pages
  10. 6y agovimAdds matchImpute() and random-forest augmented kNN
  11. 6y agovimOrdered factor support and ordinal regression in irmi()
  12. 6y agovimBug fixes for kNN, hotdeck and irmi input handling

Frequently asked questions

What is the difference between gratia and vim?

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

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

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

What are the best alternatives to vim?

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