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Titlebook: Measure Theory, Probability, and Stochastic Processes; Jean-Fran?ois Le Gall Textbook 2022 The Editor(s) (if applicable) and The Author(s)

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發(fā)表于 2025-3-21 17:12:54 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Measure Theory, Probability, and Stochastic Processes
編輯Jean-Fran?ois Le Gall
視頻videohttp://file.papertrans.cn/629/628050/628050.mp4
概述Provides a rigorous treatment of measure theory geared towards the general theory of stochastic processes.Highlights the interplay between probability and other areas of mathematics such as complex va
叢書(shū)名稱Graduate Texts in Mathematics
圖書(shū)封面Titlebook: Measure Theory, Probability, and Stochastic Processes;  Jean-Fran?ois Le Gall Textbook 2022 The Editor(s) (if applicable) and The Author(s)
描述.This textbook introduces readers to the fundamental notions of modern probability theory. The only prerequisite is a working knowledge in real analysis. Highlighting the connections between martingales and Markov chains on one hand, and Brownian motion and harmonic functions on the other, this book provides an introduction to the rich interplay between probability and other areas of analysis..Arranged into three parts, the book begins with a rigorous treatment of measure theory, with applications to probability in mind. The second part of the book focuses on the basic concepts of probability theory such as random variables, independence, conditional expectation, and the different types of convergence of random variables. In the third part, in which all chapters can be read independently, the reader will encounter three important classes of stochastic processes: discrete-time martingales, countable state-space Markov chains, and Brownian motion. Each chapter ends with a selectionof illuminating exercises of varying difficulty. Some basic facts from functional analysis, in particular on Hilbert and Banach spaces, are included in the appendix.. .Measure Theory, Probability, and Stoch
出版日期Textbook 2022
關(guān)鍵詞probability le gall; rigorous probability textbook; probability measure textbook; measure theory for pr
版次1
doihttps://doi.org/10.1007/978-3-031-14205-5
isbn_softcover978-3-031-14207-9
isbn_ebook978-3-031-14205-5Series ISSN 0072-5285 Series E-ISSN 2197-5612
issn_series 0072-5285
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Graduate Texts in Mathematicshttp://image.papertrans.cn/m/image/628050.jpg
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Signed Measuresition of a signed measure. We also state a version of the Radon-Nikodym theorem for signed measures, and, as an application, we prove an important theorem of functional analysis stating that the space .. is the topological dual of .. when . and . are conjugate exponents and .?∈?[1, .)
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Conditioninguss the discrete setting, which helps to understand the axiomatic definition of conditional expectation in the general case. The last section introduces the notion of conditional law, which is useful in this book mainly from a conceptual point of view.
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Theory of Martingales developments of advanced probability theory. We present here the basic convergence theorems for martingales. These results have important applications to other random processes, including random walks and branching processes.
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