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Non-Gaussian Selfsimilar Stochastic Processes / by Ciprian Tudor
(SpringerBriefs in Probability and Mathematical Statistics. ISSN:23654341)
版 | 1st ed. 2023. |
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出版者 | Cham : Springer Nature Switzerland : Imprint: Springer |
出版年 | 2023 |
本文言語 | 英語 |
大きさ | XII, 101 p. 1 illus : online resource |
著者標目 | *Tudor, Ciprian author SpringerLink (Online service) |
件 名 | LCSH:Probabilities FREE:Probability Theory FREE:Applied Probability |
一般注記 | Introduction -- Chapter 1. Multiple Stochastic Integrals -- Chapter 2. Hermite processes: Definition and basic properties -- Chapter 3. The Wiener integral with respect to the Hermite process and the Hermite Ornstein-Uhlenbeck process -- Chapter 4. Hermite sheets and SPDEs -- Chapter 5. Statistical inference for stochastic (partial) differential equations with Hermite noise -- References This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process in this class. Using the Wiener chaos theory and multiple stochastic integrals, the book covers the main properties of Hermite processes and their multiparameter counterparts, the Hermite sheets. It delves into the probability distribution of these stochastic processes and their sample paths, while also presenting the basics of stochastic integration theory with respect to Hermite processes and sheets. The book goes beyond theory and provides a thorough analysis of physical models driven by Hermite noise, including the Hermite Ornstein-Uhlenbeck process and the solution to the stochastic heat equation driven by such a random perturbation. Moreover, it explores up-to-date topics central to current researchin statistical inference for Hermite-driven models HTTP:URL=https://doi.org/10.1007/978-3-031-33772-7 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783031337727 |
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EB00229454 |
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データ種別 | 電子ブック |
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分 類 | LCC:QA273.A1-274.9 DC23:519.2 |
書誌ID | 4001021146 |
ISBN | 9783031337727 |