概要
This skill equips Claude with specialized knowledge for developing and auditing Bayesian hierarchical models using BUGS and JAGS. It addresses the critical precision parameterization pitfall—where BUGS uses inverse variance instead of standard deviation—and provides a complete distribution reference for continuous, discrete, and multivariate data. Whether you are building new declarative models, converting Stan code to BUGS, or integrating scripts into R workflows via R2jags, this skill ensures mathematical accuracy and syntactic correctness in your Bayesian workflows.
