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Titlebook: Applied Stochastic Processes; Mario Lefebvre Textbook 2007 Springer-Verlag New York 2007 Brownian motion.Markov.Markov chain.Poisson proce

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期刊全称Applied Stochastic Processes
影响因子2023Mario Lefebvre
视频videohttp://file.papertrans.cn/161/160176/160176.mp4
发行地址Presents carefully chosen topics such as Gaussian and Markovian processes, Markov Chains, Poisson processes, Brownian motion and queueing theory.Examines in detail special diffusion processes, with im
学科分类Universitext
图书封面Titlebook: Applied Stochastic Processes;  Mario Lefebvre Textbook 2007 Springer-Verlag New York 2007 Brownian motion.Markov.Markov chain.Poisson proce
影响因子.Applied Stochastic Processes. uses a distinctly applied framework to present the most important topics in the field of stochastic processes.. .Key features:. .-Presents carefully chosen topics such as Gaussian and Markovian processes, Markov chains, Poisson processes, Brownian motion, and queueing theory.-Examines in detail special diffusion processes, with implications for finance, various generalizations of Poisson processes, and renewal processes.-Serves graduate students in a variety of disciplines such as applied mathematics, operations research, engineering, finance, and business administration.-Contains numerous examples and approximately 350 advanced problems, reinforcing both concepts and applications. .-Includes entertaining mini-biographies of mathematicians, giving an enriching historical context. .-Covers basic results in probability. .Two appendices with statistical tables and solutions to the even-numbered problems are included at the end. This textbook is for graduate students in applied mathematics, operations research, and engineering. Pure mathematics students interested in the applications of probability and stochastic processes and students in business adminis
Pindex Textbook 2007
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978-0-387-34171-2Springer-Verlag New York 2007
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Universitexthttp://image.papertrans.cn/b/image/160176.jpg
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Applied Stochastic Processes978-0-387-48976-6Series ISSN 0172-5939 Series E-ISSN 2191-6675
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https://doi.org/10.1007/978-1-4899-1051-6 a . at time .. We suppose that the . who arrive in the system come to receive some service or to perform a certain task (for example, to withdraw money from an automated teller machine). There can be one or many . or .. The process .(.),. ≥ 0 is a model for a . or a .. If we want to be precise, the
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Jens Knudsen,Linda Chivers,Raymond Dils .(., .), . .(.),. ∈ . . . . . ..
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https://doi.org/10.1007/978-1-4684-5212-9The notion of a . was seen in Section 2.4. In the general case, the stochastic process {.(.), . ∈ .} is said to be Markovian if . for all events . and for all time instants . < ..
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