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ggstats vs haze

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

Shared themes:r-package

ggstats vs haze: at a glance

Featureggstatshaze
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesggplot2, data-visualization, likert, regression-modelsneuroimaging, mesh-processing, interpolation, r-package
Last editorial update47m ago3h ago
WebsiteVisit →Visit →

What is ggstats?

ggstats keeps widening what a coefficient or Likert plot can be

ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.

Read the full ggstats trajectory →

What is haze?

Four dormant years end with a modernization pass and an off-by-one fix in the C++ core

haze does nearest-neighbour smoothing and k-d tree interpolation on brain surface meshes. It sat untouched from April 2022 until July 2026, when a single release modernized it for current R versions and corrected an off-by-one error in the C++ code. It is not on CRAN and never will be — the package exceeds 50MB against CRAN's 5MB ceiling, a constraint its own initial release notes acknowledge.

Read the full haze trajectory →

ggstats vs haze: editorial side-by-side

G
ggstats
ANALYTICS
0.0

ggstats keeps widening what a coefficient or Likert plot can be

◆ Current state

ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.

◆ Where it's heading

Two long-running threads. The coefficient side has been consolidating — ggcoef_multinom() and ggcoef_multicomponents() soft-deprecated in favour of a unified ggcoef_model() with group_by, plus new ggcoef_dodged() and ggcoef_faceted() variants. The Likert side keeps expanding outward instead, absorbing survey objects, total columns and side-by-side layouts. Underneath both is a steady tax of ggplot2 and vctrs compatibility work, including tracking the geom_errorbarh() deprecation in ggplot2 4.0.0.

◆ Prediction

Expect gglikert_side() to lose its experimental status once its interface settles, and the deprecated multinomial entry points to be removed in a future release now that ggcoef_model() covers their cases.

H
haze
ANALYTICS
2.5

Four dormant years end with a modernization pass and an off-by-one fix in the C++ core

◆ Current state

haze does nearest-neighbour smoothing and k-d tree interpolation on brain surface meshes. It sat untouched from April 2022 until July 2026, when a single release modernized it for current R versions and corrected an off-by-one error in the C++ code. It is not on CRAN and never will be — the package exceeds 50MB against CRAN's 5MB ceiling, a constraint its own initial release notes acknowledge.

◆ Where it's heading

The July 2026 release arrived 56 minutes after its sibling regfusionr 0.3.0 from the same maintainer, which is the tell: this is a maintainer sweeping a set of related neuroimaging packages back into working order, not independent development on haze itself. haze is the dependency, regfusionr the consumer, and the substantive work sits on the regfusionr side. The off-by-one correction is the only change here that alters results.

◆ Prediction

Expect haze to move only when a downstream dfsp-spirit package needs it to — its cadence is driven by the sibling packages, not by its own roadmap.

Alternatives to ggstats and haze

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 ggstats or haze.

See all ggstats alternatives → · See all haze alternatives →

Recent activity from ggstats and haze

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

  1. 18d agohazeVersion 0.3.0 -- Fixes and modernization
  2. 5mo agoggstatsgglikert_side() and total columns for Likert plots
  3. 7mo agoggstatsLikert functions accept survey objects
  4. 11mo agoggstatsTable output for ggcoef_compare(); x-axis limits harmonised
  5. 1y agoggstatsggstats 0.10.0
  6. 1y agoggstatsCoefficient plots unified around ggcoef_model() with grouping
  7. 1y agoggstatsDiverging and Likert geoms redesigned; connector geoms added
  8. 4y agohazev0.2.0 -- kdtrees
  9. 4y agohazev0.1.0: Initial release

Frequently asked questions

What is the difference between ggstats and haze?

Both compete on the same themes — r-package — within Analytics. haze is currently shipping more aggressively (velocity 2.5 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 ggstats better than haze?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. haze is currently shipping more aggressively (velocity 2.5 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 ggstats?

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

What are the best alternatives to haze?

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