fit an ernm model
ernmFit(
sampler,
theta0,
mcmcBurnIn = 10000,
mcmcInterval = 100,
mcmcSampleSize = 10000,
minIter = 3,
maxIter = 40,
objectiveTolerance = 0.5,
gradTolerance = 0.25,
meanStats,
verbose = 1,
method = c("bounded", "newton")
)ernm object
the ErnmModel
initial starting values
burn in
interval
sample size
minimum number of iterations
maximum number of iterations
convergance criteria on change in log likelihood ratio
convergance criteria on scaled gradient
if non-missing, these are the target statistics
level of verbosity 0, 1, or 2
the optimization method to use