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Selfsimilar Processes /
The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these systems exhibit a slow correlation decay--a phenomenon often referred to as long-memory or long-range dependence. An example of this is the...
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| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Princeton, N.J. :
Princeton University Press,
2002.
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| Colección: | Book collections on Project MUSE.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 020 | |a 9781400825103 | ||
| 020 | |z 9781400814244 | ||
| 020 | |z 9781400815746 | ||
| 020 | |z 9780691096278 | ||
| 040 | |a MdBmJHUP |c MdBmJHUP | ||
| 100 | 1 | |a Embrechts, Paul, |d 1953- | |
| 245 | 1 | 0 | |a Selfsimilar Processes / |c Paul Embrechts and Makoto Maejima. |
| 264 | 1 | |a Princeton, N.J. : |b Princeton University Press, |c 2002. | |
| 264 | 3 | |a Baltimore, Md. : |b Project MUSE, |c 0000 | |
| 264 | 4 | |c ©2002. | |
| 300 | |a 1 online resource: |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 0 | |a Princeton series in applied mathematics | |
| 505 | 0 | |a Contents; Preface; Chapter 1. Introduction; Chapter 2. Some Historical Background; Chapter 3. Selfsimilar Processes with Stationary Increments; Chapter 4. Fractional Brownian Motion; Chapter 5. Selfsimilar Processes with Independent Increments; Chapter 6. Sample Path Properties of Selfsimilar Stable Processes with Stationary Increments; Chapter 7. Simulation of Selfsimilar Processes; Chapter 8. Statistical Estimation; Chapter 9. Extensions; References; Index. | |
| 520 | |a The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these systems exhibit a slow correlation decay--a phenomenon often referred to as long-memory or long-range dependence. An example of this is the absolute returns of equity data in finance. Selfsimilar stochastic processes (particularly fractional Brownian motion) have long been postulated as a means to model this behavior, and the concept of selfsimilarity for a stochastic process is now proving to be extraordinarily useful. Selfsimilarity t. | ||
| 546 | |a In English. | ||
| 588 | |a Description based on print version record. | ||
| 650 | 7 | |a Self-similar processes. |2 fast |0 (OCoLC)fst01111938 | |
| 650 | 7 | |a Distribution (Probability theory) |2 fast |0 (OCoLC)fst00895600 | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Stochastic Processes. |2 bisacsh | |
| 650 | 7 | |a distribution (statistics-related concept) |2 aat | |
| 650 | 6 | |a Distribution (Theorie des probabilites) | |
| 650 | 6 | |a Processus autosimilaires. | |
| 650 | 0 | |a Distribution (Probability theory) | |
| 650 | 0 | |a Self-similar processes. | |
| 655 | 7 | |a Electronic books. |2 local | |
| 700 | 1 | |a Maejima, Makoto. | |
| 710 | 2 | |a Project Muse. |e distributor | |
| 830 | 0 | |a Book collections on Project MUSE. | |
| 856 | 4 | 0 | |z Texto completo |u https://projectmuse.uam.elogim.com/book/31076/ |
| 945 | |a Project MUSE - Custom Collection | ||