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＜電子ブック＞
Non-Gaussian Selfsimilar Stochastic Processes / by Ciprian Tudor
(SpringerBriefs in Probability and Mathematical Statistics. ISSN:23654341)

版	1st ed. 2023.
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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