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print.mixgpd_fit() gives a compact header for a fitted one-arm model. It is meant as a quick identity check rather than a full posterior summary.

Usage

# S3 method for class 'mixgpd_fit'
print(x, ...)

Arguments

x

A fitted object of class "mixgpd_fit".

...

Unused.

Value

x invisibly.

Details

The fitted object represents posterior draws from a bulk mixture model, or from its spliced bulk-tail extension when GPD = TRUE. For the bulk part, the predictive law has the mixture form $$f(y \mid x) = \sum_{k=1}^{K} w_k(x) f_k(y \mid x, \theta_k).$$ When a GPD tail is active, exceedances above the threshold are instead routed through the generalized Pareto tail attached to the same bulk mixture.

The print method reports only the model identity and basic metadata. Use summary() for parameter-level posterior summaries, predict() for predictive functionals, and plot() for chain diagnostics.

Examples

if (FALSE) { # \dontrun{
y <- abs(stats::rnorm(50)) + 0.1
bundle <- build_nimble_bundle(y = y, backend = "sb", kernel = "normal",
                             GPD = TRUE, components = 6,
                             mcmc = list(niter = 200, nburnin = 50, thin = 1, nchains = 1))
fit <- run_mcmc_bundle_manual(bundle)
print(fit)
} # }