| 书目名称 | Stochastic Models with Power-Law Tails | | 副标题 | The Equation X = AX | | 编辑 | Dariusz Buraczewski,Ewa Damek,Thomas Mikosch | | 视频video | | | 概述 | Covers fields which are not available in book form and are spread over the literature.Provides an accessible introduction to a complicated stochastic model.A readable overview of one of the most compl | | 丛书名称 | Springer Series in Operations Research and Financial Engineering | | 图书封面 |  | | 描述 | .In this monograph the authors give a systematic approach to the probabilistic properties of the fixed point equation X=AX+B. A probabilistic study of the stochastic recurrence equation X_t=A_tX_{t-1}+B_t for real- and matrix-valued random variables A_t, where (A_t,B_t) constitute an iid sequence, is provided. The classical theory for these equations, including the existence and uniqueness of a stationary solution, the tail behavior with special emphasis on power law behavior, moments and support, is presented. The authors collect recent asymptotic results on extremes, point processes, partial sums (central limit theory with special emphasis on infinite variance stable limit theory), large deviations, in the univariate and multivariate cases, and they further touch on the related topics of smoothing transforms, regularly varying sequences and random iterative systems..The text gives an introduction to the Kesten-Goldie theory for stochastic recurrence equations of the type X_t=A_tX_{t-1}+B_t. It provides the classical results of Kesten, Goldie, Guivarc‘h, and others, and gives an overview of recent results on the topic. It presents the state-of-the-art results in the field of affin | | 出版日期 | Book 2016 | | 关键词 | Power Law Tail; Random Iterative Function System; Stochastic Recurrence Equation; Regular Variation; Kes | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-29679-1 | | isbn_softcover | 978-3-319-80624-2 | | isbn_ebook | 978-3-319-29679-1Series ISSN 1431-8598 Series E-ISSN 2197-1773 | | issn_series | 1431-8598 | | copyright | Springer International Publishing Switzerland 2016 |
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发表于 2025-3-21 18:40:37
