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Continuous Parameter Markov Processes and Stochastic Differen... - 9783031341533

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Continuous Parameter Markov Processes and Stochastic Differential EquationsAuthor(s): Rabi Bhattacharya, Edward C. Waymire\nFormat: Paperback\nPublisher: Springer International Publishing AG, Switzerland\nImprint: Springer International Publishing AG\nISBN-13: 9783031341533, 978-3031341533\nSynopsis\nThis graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications. The authors focus on developing context and intuition before formalizing the theory of each topic, illustrated with examples.\n\nAfter a review of some background material, the reader is introduced to semigroup theory, including the HilleYosida Theorem, used to construct continuous parameter Markov processes. Illustrated with examples, it is a cornerstone of Fellers seminal theory of the most general one-dimensional diffusions studied in a later chapter. This is followed by two chapters with probabilistic constructions of jump Markov processes, and processes .

Continuous Parameter Markov Processes and Stochastic Differen... - 9783031341533

Continuous Parameter Markov Processes and Stochastic Differential EquationsAuthor(s): Rabi Bhattacharya, Edward C. Waymire\nFormat: Paperback\nPublisher: Springer International Publishing AG, Switzerland\nImprint: Springer International Publishing AG\nISBN-13: 9783031341533, 978-3031341533\nSynopsis\nThis graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications. The authors focus on developing context and intuition before formalizing the theory of each topic, illustrated with examples.\n\nAfter a review of some background material, the reader is introduced to semigroup theory, including the HilleYosida Theorem, used to construct continuous parameter Markov processes. Illustrated with examples, it is a cornerstone of Fellers seminal theory of the most general one-dimensional diffusions studied in a later chapter. This is followed by two chapters with probabilistic constructions of jump Markov processes, and processes .

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