Abstract
A sequence of random variables \( X_0,X_1,... \) with values in a countable set S is a Markov chain if at any time n, the future states (or values) \( X_{n+1}, X_{n+2},... \) depend on the history \( X_0,...,X_n \) only through the present state \( X_n \).
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© 2009 Springer-Verlag Berlin Heidelberg
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Serfozo, R. (2009). Markov Chains. In: Basics of Applied Stochastic Processes. Probability and Its Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89332-5_1
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DOI: https://doi.org/10.1007/978-3-540-89332-5_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89331-8
Online ISBN: 978-3-540-89332-5
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