# NOT RUN {
# Load the florentine marriage network:
data(florentine)
flo.formula <- flomarriage ~ edges + kstar(2)
info.adjustPL <- adjustPL(formula = flo.formula,
aux.iters = 100,
noisy.nsim = 50,
noisy.thin = 50,
ladder = 30,
estimate = "MLE",
control = control.ergm(MCMC.samplesize=2000))
# Specify a prior distribution:
mean.priors <- rep(0, 2)
sigma.priors <- diag(5, 2)
# MCMC sampling and evidence estimation:
Chib.est.evidence <- evidence_CJ(formula = flo.formula,
prior.mean = mean.priors,
prior.sigma = sigma.priors,
nits = 30000,
burnin = 5000,
thin = 1,
num.samples = 25000,
tunePL = 2,
info.adjustPL = info.adjustPL)
# MCMC diagnostics and posterior summaries:
bergm.output(Chib.est.evidence)
# Log-marginal likelihood estimate:
Chib.est.evidence$log.evidence
# }
# NOT RUN {
# }
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