choxos/BayesianAgent

Foundational knowledge for writing BUGS/JAGS models including precision parameterization, declarative syntax, distributions, and R integration. Use when creating or reviewing BUGS/JAGS models.

Patterns for hierarchical/multilevel Bayesian models including random effects, partial pooling, and centered vs non-centered parameterizations.

Bayesian meta-analysis models including fixed effects, random effects, and network meta-analysis with Stan and JAGS implementations.

MCMC diagnostics for Bayesian models including convergence assessment, effective sample size, divergences, and posterior predictive checks.

Foundational knowledge for writing PyMC 5 models including syntax, distributions, sampling, and ArviZ diagnostics. Use when creating or reviewing PyMC models.

Bayesian regression models including linear, logistic, Poisson, negative binomial, and robust regression with Stan and JAGS implementations.

Foundational knowledge for writing Stan 2.37 models including program structure, type system, distributions, and best practices. Use when creating or reviewing Stan models.

Bayesian survival analysis models including exponential, Weibull, log-normal, and piecewise exponential hazard models with censoring support.

Bayesian time series models including AR, MA, ARMA, state-space models, and dynamic linear models in Stan and JAGS.