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gratia vs TidyDensity

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

Shared themes:r-package

gratia vs TidyDensity: at a glance

FeaturegratiaTidyDensity
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesgam, mgcv, ggplot2, statistical-graphicsstatistical-distributions, random-generation, parameter-estimation, tidyverse
Last editorial update49m 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 TidyDensity?

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

Read the full TidyDensity trajectory →

gratia vs TidyDensity: 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.

T
TidyDensity
ANALYTICS
0.0

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

◆ Current state

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

◆ Where it's heading

The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.

◆ Prediction

The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.

Alternatives to gratia and TidyDensity

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 TidyDensity.

See all gratia alternatives → · See all TidyDensity alternatives →

Recent activity from gratia and TidyDensity

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

  1. 11mo agoTidyDensityquantile_normalize rewritten, changing its output
  2. 11mo agogratiaggplot2 4.0.0 compatibility, plus four more quantile-residual families
  3. 1y agoTidyDensityDocumentation corrections for two distribution functions
  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 agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
  7. 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
  8. 2y agogratiaEvery generated column gains a dot prefix
  9. 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
  10. 2y agoTidyDensityDistributions convertible to time series objects
  11. 3y agogratiaReal variable names in smooth_samples(), plus dplyr 1.1.0 fixes
  12. 4y agogratiaM1 example output fixes and confint tibble returns

Frequently asked questions

What is the difference between gratia and TidyDensity?

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

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

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