getdoce65e. 142KB Jun 04 2011 12:05:07 AM
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In this paper, we study a stationary control problem when the state process is a one di- mensional diffusion whose drift admits a unique, asymptotically stable equilibrium point
In particular, when the Markov process in question is a diffusion, we obtain the integral test corresponding to a law of the iterated logarithm due to
Keywords: General state space Markov chains; f -regularity; Markov chain central limit theo- rem; Drazin inverse; fundamental matrix; asymptotic
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
Abstract: Let X and Y be time-homogeneous Markov processes with common state space E, and assume that the transition kernels of X and Y admit densities with respect to
Following [1], the velocity field could be viewed as a Ornstein-Uhlenbeck process taking values in an infinite dimensional function space.. We
Finally, we note that the proof of the convergence (3) of Theorem 2 (which is given in Section 4) works as it is, when we start the Markov chain with a translation invariant
To state the necessary and sufficient condition, we extend the notion of graph of a random matrix from the fixed support case, that is when the entries are either almost-surely finite
