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Titlebook: An Introduction to Applied Probability; Pierre Brémaud Textbook 2024 Springer Nature Switzerland AG 2024 Probability textbook.Markov chain

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發(fā)表于 2025-3-21 18:08:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱An Introduction to Applied Probability
影響因子2023Pierre Brémaud
視頻videohttp://file.papertrans.cn/156/155137/155137.mp4
發(fā)行地址Provides a clear and intuitive introduction to the range of probabilistic tools used in the applied sciences.Covers diverse topics such as random graphs, rejection sampling, and Bayesian hypothesis te
學(xué)科分類Texts in Applied Mathematics
圖書封面Titlebook: An Introduction to Applied Probability;  Pierre Brémaud Textbook 2024 Springer Nature Switzerland AG 2024 Probability textbook.Markov chain
影響因子This book provides the elements of probability and stochastic processes of direct interest to the applied sciences where probabilistic models play an important role, most notably in the information and communications sciences, computer sciences, operations research, and electrical engineering, but also in fields like epidemiology, biology, ecology, physics, and the earth sciences..The theoretical tools are presented gradually, not deterring the readers with a wall of technicalities before they have the opportunity to understand their relevance in simple situations. In particular, the use of the so-called modern integration theory (the Lebesgue integral) is postponed until the fifth chapter, where it is reviewed in sufficient detail for a rigorous treatment of the topics of interest in the various domains of application listed above..The treatment, while mathematical, maintains a balance between depth and accessibility that is suitable for theefficient manipulation, based on solid theoretical foundations, of the four most important and ubiquitous categories of probabilistic models:.Markov chains, which are omnipresent and versatile models in applied probability.Poisson processes (on
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0939-2475 olid theoretical foundations, of the four most important and ubiquitous categories of probabilistic models:.Markov chains, which are omnipresent and versatile models in applied probability.Poisson processes (on978-3-031-49306-5Series ISSN 0939-2475 Series E-ISSN 2196-9949
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https://doi.org/10.1007/978-3-031-49306-5Probability textbook; Markov chains; Discrete random variables; Random vectors; Convergence of random va
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Springer Nature Switzerland AG 2024
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Pierre BrémaudProvides a clear and intuitive introduction to the range of probabilistic tools used in the applied sciences.Covers diverse topics such as random graphs, rejection sampling, and Bayesian hypothesis te
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Texts in Applied Mathematicshttp://image.papertrans.cn/a/image/155137.jpg
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