How to determine the length of the required burn-in until convergence in MCMCglmm package or another package

We would probably need more information to help you.
  Some quick thoughts:

- MCMCglmm usually burns in very quickly.   I would guess that either
(1) your problem/data are really pathological; (2) you're confusing
"burn-in" with "mixing"; if your chain reaches the stationary state
quickly but samples it slowly, then you're having a burn-in rather
than a mixing problem.  In general PRSF is meant to diagnose
convergence, not just burn-in. (Although now that I read your
question, it sounds like it's only the title that's specific to
burn-in ...)

- I think what most people do is brute-force (increase length of
chain, increasing thinning at the same time so that the number of
samples remains constant, until traceplots look OK/PRSF looks OK).
- setting more informative priors may be helpful/necessary
- the coda package has other diagnostics, in particular the
Raftery-Lewis (raftery.diag()), which is supposed to estimate the
chain length required for convergence.  You should be able to apply it
to the components of an MCMCglmm fit ($Sol, $VCV, etc.), which are
mcmc objects

Hi,

I stil try fit linear mixed model. I use Potencial Scale Reduction (PSR) to
check convergence. But, it still dosn't convergence. Is there any function
that can i use to determine length of chains, length of burn-in, or
thinning interval?

Thank you.

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