Understanding Markov chains. Examples and applications

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Author(s): Privault, Nicolas
Series: Springer undergraduate mathematics series
Edition: 2nd edition
Publisher: Springer. copyright 2018
Year: 2018

Language: English
Pages: 372
Tags: Distribution (théorie des probabilités).;Markov, Processus de.

Content: Probability Background.- Gambling Problems.- Random Walks.- Discrete-Time Markov Chains.- First Step Analysis.- Classification of States.- Long-Run Behavior of Markov Chains.- Branching Processes.- Continuous-Time Markov Chains.- Discrete-Time Martingales.- Spatial Poisson Processes.- Reliability Theory.