[ADMB Users] mcmc with a high N

[Ian Taylor]

Hi Edgar,
You should be able to set a different random number seed for MCMC using the
-mcseed input. You can also theoretically change the starting point for the
MCMC using -mcpin. However, multiple short MCMC chains are not a
replacement for a single long chain, and if the convergence diagnostics
suggest 6 000 000 samples, I think you are very unlikely to get a good
approximation to the posterior with 12 runs of 500 000.

I would say that a more fruitful path would be to look at which parameters
were the most correlated with each other or had the most autocorrelation in
the shorter MCMC and look at reparameterizing the model or reducing the
number of parameters.
-Ian

On Thu, Jul 5, 2012 at 9:00 AM, Edgar Gonzalez <edgarjgonzalez at ymail.com>wrote:

> Hi everyone:
>
> I'm trying to run mcmc on ADMB. I ran a pre-run to estimate the Total N
> required to obtain the posterior distribution of my parameters. I got a
> rounded N of 6 000 000. As this would take weeks (months?) to do, I'd like
> to know if there is a way to partition this into 12 runs with N = 500 000
> and to assemble them into a single run. As far as I know, the mcmc involves
> random walks, but when I ran two mcmc's I got the same walk (the traces
> look the same).
>
> Thanks in advance,
>
> Edgar J. González
> Ecology and Natural Resources Dept.
> Science Faculty, UNAM
>
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