# 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 location and shape of prior distribution:
prior.mean <- rep(0, 2)
prior.sigma <- diag(5, 2)
pp.est.evidence <- evidence_PP(formula = flo.formula,
prior.mean = prior.mean,
prior.sigma = prior.sigma,
nits = 10000,
burnin = 2000,
temps = seq(0, 1, length.out = 20)^5,
info.adjustPL = info.adjustPL)
# MCMC diagnostics and posterior summaries:
bergm.output(pp.est.evidence)
# Log-marginal likelihood estimate:
pp.est.evidence$log.evidence
# }
# NOT RUN {
# }
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