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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...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2013.
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| Edición: | 1st ed. 2013. |
| Colección: | Probability and Its Applications
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.