Description Usage Arguments Details Value Note Author(s) Examples
Determines the options (number of steps, save interval, etc.) for running MCMC based on the estimated mode (maximum likelihood estimate) and parameter variancecovariance matrix
1 2  mcmc.control(mcmc = 1000, mcmc2 = 0, mcsave, mcnoscale = FALSE,
mcgrope = FALSE, mcmult = 1, mcmcpars = NULL)

mcmc 
Total number of MCMC steps 
mcmc2 
MCMC2 steps (see ADMBRE manual) 
mcsave 
Thinning interval for values saved in the PSV file. Default is

mcnoscale 
don't rescale step size for mcmc depending on acceptance rate 
mcgrope 
(double) Use a candidate distribution that is a mixture of a
multivariate normal and a fattertailed distribution with a proportion

mcmult 
Multiplier for the MCMC candidate distribution 
mcmcpars 
(character) vector of parameters to track in MCMC run.
At least one must be specified. ADMB produces two kinds of output for
MCMC. For any 
See the AD Model Builder reference manual. The mcrb
option (reduce
correlation of the Hessian when constructing the candidate distribution) and
the mcseed
options (seed for random number generator) are not yet
implemented; mcnoscale
above may not work properly
Returns a list of options suitable for passing as the
mcmc.opts
argument to do_admb
Some options (mcmc2
, etc.) that can be used in AD Model Builder
and ADMBRE may not be available
Ben Bolker
1  mcmc.control(mcmc=2000)

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