Titlebook: Understanding Markov Chains; Examples and Applica Nicolas Privault Textbook 20131st edition Springer Nature Singapore Pte Ltd. 2013 Applica

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First Step Analysis,ndom walks already treated in Chapters . and .. The main applications of first step analysis are the computation of hitting probabilities, mean hitting and absorption times, mean first return times, and average number of returns to a given state.

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Classification of States,e also examine the notions of positive and null recurrence, periodicity, and aperiodicity of such chains. Those topics will be important when analysing the long-run behavior of Markov chains in the next chapter.

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Textbook 20131st edition with some recent results on moment identities and deviation inequalities for Poisson stochastic integrals. The concepts presented are illustrated by examples and by 72 exercises and their complete solutions..

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Continuous-Time Markov Chains,ue to the use of the strong Markov property. Here we focus on the understanding of the continuous-time case by simple calculations, and we will refer to the literature for the application of the strong Markov property.

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