rstanarm: Bayesian Regression Models via Stan for R

rstanarm is an R package for Bayesian applied regression modeling, authored by Jonah Gabry. It estimates compiled regression models using the 'rstan' package, which provides an R interface to the Stan C++ library. Users specify models via customary R syntax with a formula and data.frame, plus additional arguments for priors.

Use Cases

• Implement Bayesian linear regression based on the described formula and data.frame syntax
• Perform Bayesian generalized linear modeling based on the package's support for compiled regression models
• Compare model results with different prior specifications based on the mentioned prior arguments
• Apply Bayesian inference to social or economic data using the RStan backend mentioned in the description

Strengths

• Provides a bridge to the Stan probabilistic programming language via the established 'rstan' package
• Leverages familiar R syntax for model specification, potentially reducing the learning curve

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

Software package for statistical estimation.

Time Range

Temporal coverage is not specified.

Freshness

Last updated date is unknown.

Geography

Spatial coverage is not specified.