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Titlebook: Approximation Methods in Probability Theory; Vydas ?ekanavi?ius Textbook 2016 Springer International Publishing Switzerland 2016 character

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樓主
發(fā)表于 2025-3-21 18:18:27 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Approximation Methods in Probability Theory
影響因子2023Vydas ?ekanavi?ius
視頻videohttp://file.papertrans.cn/161/160389/160389.mp4
發(fā)行地址Presents a unique collection of approximation methods in various metrics.Explains the essential aspects of each method in detail.Includes many exercises with solutions as well as bibliographical notes
學(xué)科分類Universitext
圖書封面Titlebook: Approximation Methods in Probability Theory;  Vydas ?ekanavi?ius Textbook 2016 Springer International Publishing Switzerland 2016 character
影響因子.This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function. Emphasising the correct usage of the methods presented, each step required for the proofs is examined in detail. As a result, this textbook provides valuable tools for proving approximation theorems...While .Approximation Methods in Probability Theory. will appeal to everyone interested in limit theorems of probability theory, the book is particularly aimed at graduate students who have completed a standard intermediate course in probability theory. Furthermore, experienced researchers wanting to enlarge their toolkit will also find this book useful..
Pindex Textbook 2016
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沙發(fā)
發(fā)表于 2025-3-21 20:33:19 | 只看該作者
The Stein Method,d to consult the books and papers referenced at the end of this chapter. Here we present just a basic idea of how the method works for the normal approximation and a short introduction to lattice random variables. On the other hand, we include some results that might be viewed as complementary mater
板凳
發(fā)表于 2025-3-22 01:00:04 | 只看該作者
Vydas ?ekanavi?iusPresents a unique collection of approximation methods in various metrics.Explains the essential aspects of each method in detail.Includes many exercises with solutions as well as bibliographical notes
地板
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Universitexthttp://image.papertrans.cn/b/image/160389.jpg
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發(fā)表于 2025-3-22 12:17:41 | 只看該作者
https://doi.org/10.1007/978-3-319-34072-2characteristic function; compound distribution; inversion formula; Kerstan‘s method; m-dependent variabl
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Marketing und Innovationsmanagementd to consult the books and papers referenced at the end of this chapter. Here we present just a basic idea of how the method works for the normal approximation and a short introduction to lattice random variables. On the other hand, we include some results that might be viewed as complementary mater
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