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ggstatsplot vs hdnom

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

ggstatsplot vs hdnom: at a glance

Featureggstatsplothdnom
SectorAnalyticsAnalytics
Velocity score0.05.0
Sparks · 30d00
Top themesstatistical-plots, ggplot2, contingency-tables, hypothesis-testingsurvival analysis, r, regularization, nomograms
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is ggstatsplot?

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

Read the full ggstatsplot trajectory →

What is hdnom?

hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to

hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.

Read the full hdnom trajectory →

ggstatsplot vs hdnom: editorial side-by-side

G
ggstatsplot
ANALYTICS
0.0

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

◆ Current state

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

◆ Where it's heading

The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.

◆ Prediction

Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.

H
hdnom
ANALYTICS
5.0

hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to

◆ Current state

hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.

◆ Where it's heading

The releases track two upstream pressures with no feature work of its own. glmnet is the larger one: its 4.1-9 change to how Cox cross-validation errors are normalized made lambda.1se select null models far more often, forcing hdnom to expose a rule argument and switch its examples to lambda.min. R-devel is the other, producing a steady trickle of strict-headers, deprecated-symbol and check-note fixes. The pattern is consistent — absorb the upstream change, default to whatever preserves existing behaviour, let users opt into the new one.

◆ Prediction

The cox.ties default is explicitly pinned to "breslow" to silence glmnet's migration warning, which is a deferral rather than a decision; expect a future release to flip that default to "efron" once glmnet completes the transition.

Alternatives to ggstatsplot and hdnom

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 ggstatsplot or hdnom.

See all ggstatsplot alternatives → · See all hdnom alternatives →

Recent activity from ggstatsplot and hdnom

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

  1. 18d agohdnomhdnom 6.2.1
  2. 18d agohdnomhdnom 6.2.0 pins Cox tie handling ahead of glmnet's migration
  3. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  4. 4mo agoggstatsplotInternal maintenance only
  5. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  6. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  7. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  8. 11mo agoggstatsplotAdapted to the latest ggplot2 release
  9. 1y agohdnomhdnom 6.1.0 exposes lambda selection after a glmnet normalization change
  10. 1y agohdnomhdnom 6.0.4
  11. 2y agohdnomhdnom 6.0.3
  12. 3y agohdnomhdnom 6.0.2

Frequently asked questions

What is the difference between ggstatsplot and hdnom?

They serve adjacent needs but don't currently overlap on shipped themes. hdnom is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is ggstatsplot better than hdnom?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hdnom is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to ggstatsplot?

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

What are the best alternatives to hdnom?

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