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Titlebook: Normal Approximation by Stein’s Method; Louis H.Y. Chen,Larry Goldstein,Qi-Man Shao Textbook 2011 Springer-Verlag GmbH Berlin Heidelberg 2

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書(shū)目名稱Normal Approximation by Stein’s Method
編輯Louis H.Y. Chen,Larry Goldstein,Qi-Man Shao
視頻videohttp://file.papertrans.cn/669/668019/668019.mp4
概述First book that presents a complete self-contained treatment of Stein‘s method.Includes many recent applications.Important reference for researchers and suitable for graduate student seminars.Includes
叢書(shū)名稱Probability and Its Applications
圖書(shū)封面Titlebook: Normal Approximation by Stein’s Method;  Louis H.Y. Chen,Larry Goldstein,Qi-Man Shao Textbook 2011 Springer-Verlag GmbH Berlin Heidelberg 2
描述Since its introduction in 1972, Stein’s method has offered a completely novel way of evaluating the quality of normal approximations. Through its characterizing equation approach, it is able to provide approximation error bounds in a wide variety of situations, even in the presence of complicated dependence. Use of the method thus opens the door to the analysis of random phenomena arising in areas including statistics, physics, and molecular biology. Though Stein‘s method for normal approximation is now mature, the literature has so far lacked a complete self contained treatment. This volume contains thorough coverage of the method’s fundamentals, includes a large number of recent developments in both theory and applications, and will help accelerate the appreciation, understanding, and use of Stein‘s method by providing the reader with the tools needed to apply it in new situations. It addresses researchers as well as graduate students in Probability, Statistics and Combinatorics.
出版日期Textbook 2011
關(guān)鍵詞60F05, 60B12, 62E17; Berry-Esseen bound, non-linear statistics; Stein’s method; exchangable pair, moder
版次1
doihttps://doi.org/10.1007/978-3-642-15007-4
isbn_softcover978-3-642-26565-5
isbn_ebook978-3-642-15007-4Series ISSN 1431-7028
issn_series 1431-7028
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2011
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Non-normal Approximation,statistical physics, at the critical inverse temperature, by a distribution with density proportional to exp?(?../12). Bounds for approximation by the exponential distribution are also derived, and applied to the spectrum of the Bernoulli Laplace Markov chain, and first passage times for Markov chains.
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,Berry–Esseen Bounds for Independent Random Variables,st by concentration inequalities, then by induction. This chapter concludes with a lower bound for the Berry–Esseen inequality. As seen in the chapter dependency diagram that follows, Chaps. 2 and 3 form much of the basis of this book.
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,, by Bounded Couplings,n . and ., a small bound being a reflection of a small distance. The chapter concludes with the use of smoothing inequalities to obtain distances between . and the normal over general function classes, one special case being the derivation of Kolmogorov distance bounds when bounded size bias couplings exist.
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,, Bounds,and applied to the approximation of the distribution of the volume covered by randomly placed spheres in the Euclidean torus. Results are then given for sums of locally dependent random variables, with applications including the number of local maxima on a graph. The chapter concludes with a conside
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