SIMULATING THE INVARIANT-MEASURES OF MARKOV-CHAINS USING BACKWARD COUPLING AT REGENERATION TIMES

We develop an algorithm for simulating approximate random samples from the invariant measure of a Markov chain using backward coupling of em bedded regeneration times. Related methods have been used effectively for finite chains and for stochastically monotone chains: here we prop ose a method of implementation which avoids these restrictions by usin g a ''cycle-length'' truncation. We show that the coupling times have good theoretical properties and describe benefits and difficulties of implementing the methods in practice.