ergmm
fitting. Typically only used when calling ergmm
. It is used to
set parameters that affect the sampling but do not affect the posterior distribution.ergmm.control(samplesize=2000,
burnin=1000,
interval=10,
threads=1,
mle.maxit=400,
tune=FALSE,
tuning.runs=100,
tuning.runsize=8,
Z.delta=0.4,
Z.tr.delta=0.4,
Z.scl.delta=0.02,
beta.delta=0.4,
store.burnin=FALSE)
snowFT
is used to take
advantage of any multiprocessing or distributed computing
capabilities that may be available.TRUE
, the proposal variances are tuned before
burnin and again before sampling begins. The tuner is somewhat experimental.TRUE
, the samples from the burnin are
also stored and returned, to be used in MCMC diagnostics.ergmm
data(sampson)
## Shorter run than default.
ergmm(samplike~latent(d=2,G=3),control=ergmm.control(samplesize = 200))
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