ggdist: Visualizations of Distributions and Uncertainty for Statistical Modeling

A collection of visualization primitives for the 'ggplot2' R package, designed to represent statistical distributions and uncertainty. The package, authored by Matthew Kay, supports both frequentist and Bayesian modes, handling analytical distributions and sample-based representations. It includes methods such as eye plots, quantile dot plots, and fit curves with multiple uncertainty ribbons.

Use Cases

• Visualizing Bayesian posterior samples or frequentist confidence distributions based on the described support for sample-based and analytical distributions.
• Creating publication-ready plots of uncertainty intervals, such as points with multiple intervals or fit curves with ribbons, as mentioned in the description.
• Communicating statistical results using specialized visualizations like eye plots, quantile dot plots, or complementary cumulative distribution function barplots referenced in the description.

Strengths

• Provides a unified toolkit for visualizing both frequentist and Bayesian uncertainty, as explicitly stated.
• Implements several established visualization methods, citing specific academic papers for eye plots, dot plots, and quantile dot plots.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and dataset size are unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Matthew Kay

Collection Method

Software package providing visualization primitives for the R ecosystem.

Time Range

null

Freshness

Last updated date is unknown.

Geography

null