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gratia vs svines

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

Shared themes:r-package

gratia vs svines: at a glance

Featuregratiasvines
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesgam, mgcv, ggplot2, statistical-graphicsvine-copulas, time-series, dependence-modelling, rcpp
Last editorial update1h ago1h 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 svines?

Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.

svines fits stationary vine copula models to multivariate time series, extending the rvinecopulib engine with the serial dependence structure that makes vines usable for temporal data. The visible history is three releases carrying one real addition — pseudo-residual computation and logLik support at 0.2.2 — with the rest tracking its C++ dependency.

Read the full svines trajectory →

gratia vs svines: 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.

S
svines
ANALYTICS
0.0

Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.

◆ Current state

svines fits stationary vine copula models to multivariate time series, extending the rvinecopulib engine with the serial dependence structure that makes vines usable for temporal data. The visible history is three releases carrying one real addition — pseudo-residual computation and logLik support at 0.2.2 — with the rest tracking its C++ dependency.

◆ Where it's heading

This package moves when rvinecopulib moves. The 0.2.4 release exists solely to adapt to a new rvinecopulib version, and 0.2.7 carries auto-generated GitHub release notes with no description at all. It shipped on the same day as kde1d 1.1.1, another package from the same maintainer, which is the pattern to watch: changes in the shared C++ layer surface as near-simultaneous releases across the vine family rather than as independent work.

◆ Prediction

The next release most plausibly follows another rvinecopulib update rather than adding modelling capability. Two of the three visible entries carry no substantive notes, so this feed will keep underreporting what changed.

Alternatives to gratia and svines

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 svines.

See all gratia alternatives → · See all svines alternatives →

Recent activity from gratia and svines

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

  1. 11mo agogratiaggplot2 4.0.0 compatibility, plus four more quantile-residual families
  2. 1y agosvinessvines 0.2.7
  3. 1y agosvinesAdapted to new rvinecopulib version
  4. 1y agogratiaconditional_values() replaces vis.gam for conditional prediction plots
  5. 2y agogratiaparametric_effects() joins the dot-prefix rename; LSS families begin
  6. 2y agogratiaEvery generated column gains a dot prefix
  7. 2y agosvinesPseudo residuals and logLik support added
  8. 3y agogratiaReal variable names in smooth_samples(), plus dplyr 1.1.0 fixes
  9. 4y agogratiaM1 example output fixes and confint tibble returns

Frequently asked questions

What is the difference between gratia and svines?

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

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

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