Description Usage Arguments Details Theory References See Also
This plot shows the evolution of Gelman and Rubin's shrink factor as the number of iterations increases.
1 2 3 
x 
an mcmc object 
bin.width 
Number of observations per segment, excluding the first segment which always has at least 50 iterations. 
max.bins 
Maximum number of bins, excluding the last one. 
confidence 
Coverage probability of confidence interval. 
transform 
Automatic variable transformation (see 
autoburnin 
Remove first half of sequence (see 
auto.layout 
If 
ask 
Prompt user before displaying each page of plots. Default is

col 
graphical parameter (see 
lty 
graphical parameter (see 
xlab 
graphical parameter (see 
ylab 
graphical parameter (see 
type 
graphical parameter (see 
... 
further graphical parameters. 
The Markov chain is divided into bins according to the arguments
bin.width
and max.bins
. Then the GelmanRubin shrink factor
is repeatedly calculated. The first shrink factor is calculated with
observations 1:50, the second with observations 1:(50+bin.width),
the third contains samples 1:(50+2*bin.width) and so on.
If the chain has less than 50 + bin.width iterations then
gelman.diag
will exit with an error.
A potential problem with gelman.diag
is that it may misdiagnose
convergence if the shrink factor happens to be close to 1 by chance.
By calculating the shrink factor at several points in time,
gelman.plot
shows if the shrink factor has really converged, or
whether it is still fluctuating.
Brooks, S P. and Gelman, A. (1998) General Methods for Monitoring Convergence of Iterative Simulations. Journal of Computational and Graphical Statistics, 7, 434455.
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