Run posterior sampling from a prepared bundle

mcmc() is the generic workflow runner. It dispatches to run_mcmc_bundle_manual for one-arm bundles and to run_mcmc_causal for causal bundles.

Usage

mcmc(b, ...)

Arguments

b

A non-causal or causal bundle.

...

Optional MCMC overrides (niter, nburnin, thin, nchains, seed, waic) and runner controls (show_progress, quiet).

Value

A fitted object of class "mixgpd_fit" or "causalmixgpd_causal_fit".

Details

This wrapper is useful when you want a two-stage workflow: build first, inspect or modify the bundle, then sample. Named MCMC arguments supplied through ... override the settings stored in the bundle before execution.

The returned fit represents posterior draws from the finite SB/CRP approximation encoded in the bundle. Downstream summaries therefore target posterior predictive quantities such as \(f(y \mid x)\), \(F(y \mid x)\), and derived treatment-effect functionals.

See also

bundle, run_mcmc_bundle_manual, run_mcmc_causal, predict.mixgpd_fit.