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  • 1
    UID:
    gbv_1761810030
    Format: 1 Online-Ressource (XIV, 252 Seiten)
    ISBN: 9783030704476
    Series Statement: Probability theory and stochastic modelling volume 100
    Content: This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Deterministic Markov Processes (PDMPs). A PDMP models a deterministic mechanism modified by jumps that occur at random times. The fields of applications are numerous : insurance and risk, biology, communication networks, dependability, supply management, etc. Indeed, the PDMPs studied so far are in fact deterministic functions of CSMPs (Completed Semi-Markov Processes), i.e. semi-Markov processes completed to become Markov processes. This remark leads to considerably broaden the definition of PDMPs and allows their properties to be deduced from those of CSMPs, which are easier to grasp. Stability is studied within a very general framework. In the other chapters, the results become more accurate as the assumptions become more precise. Generalized Chapman-Kolmogorov equations lead to numerical schemes. The last chapter is an opening on processes for which the deterministic flow of the PDMP is replaced with a Markov process. Marked point processes play a key role throughout this book.
    Note: Tools -- Markov renewal processes and related processes -- First steps with PDMP -- Hitting time distribution -- Intensity of some marked point pocesses -- Generalized Kolmogorov equations -- A martingale approach -- Stability -- Numerical methods -- Switching Processes -- Tools -- Interarrival distribution with several Dirac measures -- Algorithm convergence's proof.
    Additional Edition: ISBN 9783030704469
    Additional Edition: ISBN 9783030704483
    Additional Edition: ISBN 9783030704490
    Additional Edition: Erscheint auch als Druck-Ausgabe Cocozza-Thivent, Christiane Markov renewal and piecewise deterministic processes Cham, Switzerland : Springer Nature, 2021 ISBN 9783030704469
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Markov-Prozess
    URL: Cover
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