This function prints diagnistic information and creates simple diagnostic plots for the MCMC sampled
statistics produced from a stergm
fit.
1 2 3 4 5 6 
object 
A stergm object. See documentation for

center 
Logical: If TRUE, ; center the samples on the observed statistics. 
curved 
Logical: If TRUE, summarize the curved statistics (evaluated at the MLE of any nonlinear parameters), rather than the raw components of the curved statistics. 
vars.per.page 
Number of rows (one variable per row)
per plotting page. Ignored
if 
... 
Additional arguments, to be passed to plotting functions. 
The plots produced are a trace of the sampled output and a density estimate for each variable in the chain. The diagnostics printed include correlations and convergence diagnostics.
In fact, an object
contains the matrix of
statistics from the MCMC run as component $sample
.
This matrix is actually an object of class mcmc
and
can be used directly in the coda
package to assess MCMC
convergence. Hence all MCMC diagnostic methods available
in coda
are available directly. See the examples and
http://www.mrcbsu.cam.ac.uk/software/bugs/thebugsprojectwinbugs/codareadme/.
More information can be found by looking at the documentation of
stergm
.
mcmc.diagnostics.ergm
returns
some degeneracy information, if it is included in the original
object. The function is mainly used for its side effect, which is
to produce plots and summary output based on those plots.
Raftery, A.E. and Lewis, S.M. (1992). One long run with diagnostics: Implementation strategies for Markov chain Monte Carlo. Statistical Science, 7, 493497.
Raftery, A.E. and Lewis, S.M. (1995). The number of iterations, convergence diagnostics and generic Metropolis algorithms. In Practical Markov Chain Monte Carlo (W.R. Gilks, D.J. Spiegelhalter and S. Richardson, eds.). London, U.K.: Chapman and Hall.
This function is based on the coda
package
It is based on the the
R function raftery.diag
in coda
. raftery.diag
,
in turn, is based on the FORTRAN program gibbsit
written by
Steven Lewis which is available from the Statlib archive.
ergm
, stergm
,network
package,
coda
package,
summary.ergm
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs with the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.