[bachmeier]

I agree, but his argument is that in general doing a burn-in is still not going to be a substitute for good starting values, and if anything it's even easier to get a bad starting value using burn-in on a difficult problem.

[radford-neal]

If you have some nice idea of how to find a good starting value, then you should certainly use it, not just rely on burn-in.

But having used your good starting value, you should still discard some burn-in iterations. This is certainly true if you're running more than one chain, since including them all with this same starting value will bias the results (in a real, not just theoretical sense, though the magnitude of the bias will of course vary with your problem). Even if you're running just one chain, you should discard at least some burn-in (say 5%) even if you have no evidence that it is necessary, because you really don't know that your supposed good starting point is actually representative. (That is, you don't know this a difficult problems, which are the ones I'm discussing.)