Thank you Uwe for the clarification. Alan Kelly
On 24.02.2011 17:48, Alan Kelly wrote: > Deal all, as MCMClogit does not allow for the specification of several > chains, I have run my model 3 times with different random number seeds and > differently dispersed multivariate normal priors. > For example: > res1 = MCMClogit(y~x,b0=0,B0=0.001,data=mydat, burnin=500, mcmc=5500, > seed=1234, thin=5) > res2 = MCMClogit(y~x,b0=1,B0=0.01,data=mydat, burnin=500, mcmc=5500, > seed=5678, thin=5) > res3 = MCMClogit(y~x,b0=5,B0=0.0001,data=mydat, burnin=500, mcmc=5500, > seed=91011, thin=5) > > Each result produces an object of class mcmc. > In order to use the Gelman-Rubin diagnostic test via coda, I need to > "combine" these 3 mcmc objects appropriately. I thought that this would be > possible using as.mcmc.list() as the function description says: > The function ?mcmc.list? is used to represent parallel runs of the same > chain, with different starting values and random seeds. The list must be > balanced: each chain in the list must have the same iterations and the same > variables. > So I try the following: > res123=as.mcmc.list(res1, res2, res3) Use mcmc.list() rather than as.mcmc.list(). The latter is for conversion, not a constructor from separate mcmc objects. Uwe Ligges ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
