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**Practical Regeneration for Markov Chain Monte Carlo Simulation**

**Anthony E. Brockwell and Joseph B. Kadane**

### Abstract:

Regeneration is a useful tool in Markov chain Monte Carlo
simulation, since it can be used to side-step the burn-in
problem and to construct estimates of the variance of
parameter estimates themselves.
Unfortunately, it is often difficult to
take advantage of, since for most
chains, no recurrent atom exists, and it is not
always easy to use Nummelin's splitting method
to identify regeneration points.
This paper describes a simple and practical method
of obtaining regeneration in a Markov chain.
The application of this method in
simulation is discussed, and examples
are given.

*Heidi Sestrich*

*9/18/2001*
Here is the full text for this
technical report as a .pdf file.