getdoc02eb. 120KB Jun 04 2011 12:04:01 AM
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Abstract We consider Markov chains on the space of (countable) partitions of the interval [0 , 1], obtained first by size biased sampling twice (allowing repetitions) and then
Central limit theorems for Markov chains are considered, and in particular the relationships between various expressions for asymptotic variance known from the literature.. These
Furthermore, we discuss the equivalence of uniqueness criteria for chains and fields and we establish bounds for the continuity rates of the respective systems of
The most successful techniques in the quantitative study of (time homogeneous) finite Markov chains include: coupling, strong stationary time, spectral methods, and
A question of increasing importance in the Markov chain Monte Carlo literature (Gelfand and Smith, 1990; Smith and Roberts, 1993) is the issue of geometric ergodicity of Markov
Returning to the setting of finite Markov chains, it was mentioned above that the random transposition random walk on the symmetric group S n was the first example for which a
Central limit theorems for functionals of general state space Markov chains are of crucial importance in sensible implementation of Markov chain Monte Carlo algorithms as well as
For a given ordinary differential equation we propose a method consisting in a sequence of Markov chains to approximate its solution, where each of these chains minus its
