Titlebook: Matrix-Exponential Distributions in Applied Probability; Mogens Bladt,Bo Friis Nielsen Textbook 2017 Springer Science+Business Media LLC 2

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Phase-Type Distributions,osed to deduction in the general class of matrix-exponential distributions, where more . methods may be necessary. The probabilistic reasoning provides both elegance and power to the theory of matrix-exponential methods and to applications in stochastic modeling.

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Martingales and More General Markov Processes,her with their extensions to sub- and supermartingales, appear all over in stochastic modeling, and they provide us with powerful tools and techniques for addressing questions such as convergence of stochastic processes, limiting distributions, and methods related to stopping times (optional stopping theorems).

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Random Walks,By a random walk . on . we understand a stochastic process in discrete time for which ..?=?0, and for .?≥?1,where ..,?..,?… are i.i.d.??～?. for some distribution . on ..

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https://doi.org/10.1007/978-1-4939-7049-0Applied probability; Markov Processes; Matrix--exponential distributions; Numerical methods; Stochastic