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ON SIMULATING A MARKOV CHAIN STATIONARY DISTRIBUTION WHEN TRANSITION PROBABILITIES ARE UNKNOWN
Abstract
Abstract
We present an algorithm which,
given a n-state Markov chain whose steps can be simulated,
outputs a random state whose distribution is within of the
stationary distribution,
using O(n) space and O(
²
) time,
where
is a certain ``average hitting time" parameter
of the chain.
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