Discrete Time Markov Chains

Rinaldo B. Schinazi
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Rinaldo B. Schinazi: University of Colorado, Department of Mathematics

Chapter I in Classical and Spatial Stochastic Processes, 1999, pp 1-41 from Springer

Abstract: Abstract What is in this chapter? We consider a sequence of random variables (Xn)n≥1 defined on the same probability space and having countably many possible values. We think of X n as being the state of a certain system at time n. Given that Xn-1 is in some state i then X n will be in some state j with a probability denoted by p(i, j); the transition probabilities p(i, j) are built in the model. The fact that given Xn-1 we may compute the distribution of X n (we do not need to know the X k for k

Date: 1999
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-1582-0_1

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DOI: 10.1007/978-1-4612-1582-0_1

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