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As an application of Proposition 2.1, in Corollary 2.1 we also obtain two results on the total occupation time and the almost sure local extinction of the empirical measure process
Shao (2009), the inequality (1.2) has been applied to prove the necessary upper and lower bounds in Theorem 8.6 in order to obtain the moderate deviation result for
To this end we introduce a comparison finite state Markov chain which will be “close” to the non-Markov process obtained by looking at the n sites to the left of the rightmost
In Section 3 we give two examples, showing that this result allows to obtain computationally feasible formulas for the price bounds of contingent claims in general discrete-time
Key words: Multivariate and functional central limit theorems, random fields, martingale limit theorems, self-interacting Markov chains, Markov chain Monte Carlo methods,
Keywords: General state space Markov chains; f -regularity; Markov chain central limit theo- rem; Drazin inverse; fundamental matrix; asymptotic
Keywords: Pinning Model; Polymer Model; Linear Chain Model; Phase Transition; Localization Phenomena; Gradient Interaction; Laplacian Interaction; Free Energy; Markov
Keywords Central Limit Theorem (CLT), Large Deviations Principle (LDP), Markov Pro- cesses, Autoregressive Model (AR1), Positive Recurrent Processes, Martingale Additive Func-
