Bayesplot: Plotting Functions for Bayesian Model Diagnostics

Bayesplot provides a suite of plotting functions for posterior analysis, MCMC diagnostics, and predictive checks, supporting the applied Bayesian workflow. The package is designed by Jonah Gabry to offer convenient functionality for users and a common set of tools for developers of R packages for Bayesian modeling. It is particularly intended for use with packages interfacing with the 'Stan' probabilistic programming language.

Use Cases

• Visualizing posterior distributions based on the package's core plotting functions.
• Conducting MCMC diagnostics to assess sampler convergence and performance.
• Performing prior and posterior predictive checks to evaluate model fit.
• Developing standardized visualizations for new Bayesian modeling packages based on the common function set.

Strengths

• Designed to support a specific, peer-reviewed applied Bayesian workflow (Gabry et al., 2019).
• Intended as a common function set for developers, promoting standardization across R packages.

Limitations

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

Provenance

Source

Jonah Gabry

Collection Method

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Time Range

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Freshness

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Geography

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