Analysis of variations for self-similar processes : a stochastic calculus approach
Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades. This book presents the basic properties of these processes and focuses on the study of their variation using stochastic analy...
保存先:
| 第一著者: | |
|---|---|
| フォーマット: | Livre numérique |
| 言語: | Anglais |
| 出版事項: |
Cham :
Springer International Publishing
[20..].
Cham : Springer Nature |
| 版: | 1st ed. 2013. |
| シリーズ: | Probability and Its Applications
|
| オンライン･アクセス: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 注記: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Analysis of Variations for Self-similar Processes, Texte imprimé, 9783319033686 • Analysis of Variations for Self-similar Processes, Texte imprimé, 9783319009377 • Analysis of variations for self-similar processes, a stochastic calculus approach, Ciprian A. Tudor, Cham, Springer, 2013, 1 vol. (XI-268 p.), Probability and its applications, 978-3-319-00935-3 |
目次:
- Preface Introduction Part I Examples of Self-Similar Processes 1.Fractional Brownian Motion and Related Processes 2.Solutions to the Linear Stochastic Heat and Wave Equation 3.Non Gaussian Self-Similar Processes 4.Multiparameter Gaussian Processes Part II Variations of Self-Similar Process: Central and Non-Central Limit Theorems 5.First and Second Order Quadratic Variations. Wavelet-Type Variations 6.Hermite Variations for Self-Similar Processes Appendices: A.Self-Similar Processes with Stationary Increments: Basic Properties B.Kolmogorov Continuity Theorem C.Multiple Wiener Integrals and Malliavin Derivatives References Index