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...
Gespeichert in:
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Princeton, N.J. :
Princeton University Press,
©2002.
|
| Schriftenreihe: | Princeton series in applied mathematics.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 online resource (x, 111 pages) : illustrations |
| Bibliographie: | Includes bibliographical references (pages 101-108) and index. |
| ISBN: | 1400814243 9781400814244 9781400825103 1400825105 |
Internformat
MARC
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| 100 | 1 | |a Embrechts, Paul, |d 1953- |1 https://id.oclc.org/worldcat/entity/E39PBJdcv8rhpCWw8YwFxGC84q |0 http://id.loc.gov/authorities/names/n97028002 | |
| 245 | 1 | 0 | |a Selfsimilar processes / |c Paul Embrechts and Makoto Maejima. |
| 260 | |a Princeton, N.J. : |b Princeton University Press, |c ©2002. | ||
| 300 | |a 1 online resource (x, 111 pages) : |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 | 1 | |a Princeton series in applied mathematics | |
| 504 | |a Includes bibliographical references (pages 101-108) and index. | ||
| 588 | 0 | |a Print version record. | |
| 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. | ||
| 650 | 0 | |a Self-similar processes. |0 http://id.loc.gov/authorities/subjects/sh2003001114 | |
| 650 | 0 | |a Distribution (Probability theory) |0 http://id.loc.gov/authorities/subjects/sh85038545 | |
| 650 | 6 | |a Processus autosimilaires. | |
| 650 | 6 | |a Distribution (Théorie des probabilités) | |
| 650 | 7 | |a distribution (statistics-related concept) |2 aat | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Stochastic Processes. |2 bisacsh | |
| 650 | 7 | |a Distribution (Probability theory) |2 fast | |
| 650 | 7 | |a Self-similar processes |2 fast | |
| 653 | |a Almost surely. | ||
| 653 | |a Approximation. | ||
| 653 | |a Asymptotic analysis. | ||
| 653 | |a Autocorrelation. | ||
| 653 | |a Autoregressive conditional heteroskedasticity. | ||
| 653 | |a Autoregressive-moving-average model. | ||
| 653 | |a Availability. | ||
| 653 | |a Benoit Mandelbrot. | ||
| 653 | |a Brownian motion. | ||
| 653 | |a Central limit theorem. | ||
| 653 | |a Change of variables. | ||
| 653 | |a Computational problem. | ||
| 653 | |a Confidence interval. | ||
| 653 | |a Correlogram. | ||
| 653 | |a Covariance matrix. | ||
| 653 | |a Data analysis. | ||
| 653 | |a Data set. | ||
| 653 | |a Determination. | ||
| 653 | |a Fixed point (mathematics). | ||
| 653 | |a Foreign exchange market. | ||
| 653 | |a Fractional Brownian motion. | ||
| 653 | |a Function (mathematics). | ||
| 653 | |a Gaussian process. | ||
| 653 | |a Heavy-tailed distribution. | ||
| 653 | |a Heuristic method. | ||
| 653 | |a High frequency. | ||
| 653 | |a Inference. | ||
| 653 | |a Infimum and supremum. | ||
| 653 | |a Instance (computer science). | ||
| 653 | |a Internet traffic. | ||
| 653 | |a Joint probability distribution. | ||
| 653 | |a Likelihood function. | ||
| 653 | |a Limit (mathematics). | ||
| 653 | |a Linear regression. | ||
| 653 | |a Log-log plot. | ||
| 653 | |a Marginal distribution. | ||
| 653 | |a Mathematica. | ||
| 653 | |a Mathematical finance. | ||
| 653 | |a Mathematics. | ||
| 653 | |a Methodology. | ||
| 653 | |a Mixture model. | ||
| 653 | |a Model selection. | ||
| 653 | |a Normal distribution. | ||
| 653 | |a Parametric model. | ||
| 653 | |a Power law. | ||
| 653 | |a Probability theory. | ||
| 653 | |a Publication. | ||
| 653 | |a Random variable. | ||
| 653 | |a Regime. | ||
| 653 | |a Renormalization. | ||
| 653 | |a Result. | ||
| 653 | |a Riemann sum. | ||
| 653 | |a Self-similar process. | ||
| 653 | |a Self-similarity. | ||
| 653 | |a Simulation. | ||
| 653 | |a Smoothness. | ||
| 653 | |a Spectral density. | ||
| 653 | |a Square root. | ||
| 653 | |a Stable distribution. | ||
| 653 | |a Stable process. | ||
| 653 | |a Stationary process. | ||
| 653 | |a Stationary sequence. | ||
| 653 | |a Statistical inference. | ||
| 653 | |a Statistical physics. | ||
| 653 | |a Statistics. | ||
| 653 | |a Stochastic calculus. | ||
| 653 | |a Stochastic process. | ||
| 653 | |a Technology. | ||
| 653 | |a Telecommunication. | ||
| 653 | |a Textbook. | ||
| 653 | |a Theorem. | ||
| 653 | |a Time series. | ||
| 653 | |a Variance. | ||
| 653 | |a Wavelet. | ||
| 653 | |a Website. | ||
| 700 | 1 | |a Maejima, Makoto. | |
| 758 | |i has work: |a Selfsimilar processes (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGfJ8YwQ7Gc8Wk4t4Wpybd |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Embrechts, Paul, 1953- |t Selfsimilar processes. |d Princeton, N.J. : Princeton University Press, ©2002 |z 0691096279 |w (DLC) 2002108314 |w (OCoLC)48837321 |
| 830 | 0 | |a Princeton series in applied mathematics. |0 http://id.loc.gov/authorities/names/no2002046464 | |
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Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-ocm52255009 |
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| _version_ | 1816881607239270400 |
| adam_text | |
| any_adam_object | |
| author | Embrechts, Paul, 1953- |
| author2 | Maejima, Makoto |
| author2_role | |
| author2_variant | m m mm |
| author_GND | http://id.loc.gov/authorities/names/n97028002 |
| author_facet | Embrechts, Paul, 1953- Maejima, Makoto |
| author_role | |
| author_sort | Embrechts, Paul, 1953- |
| author_variant | p e pe |
| building | Verbundindex |
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| callnumber-first | Q - Science |
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| contents | 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. |
| ctrlnum | (OCoLC)52255009 |
| dewey-full | 519.23 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.23 |
| dewey-search | 519.23 |
| dewey-sort | 3519.23 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-ocm52255009 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:15:24Z |
| institution | BVB |
| isbn | 1400814243 9781400814244 9781400825103 1400825105 |
| language | English |
| oclc_num | 52255009 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (x, 111 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2002 |
| publishDateSearch | 2002 |
| publishDateSort | 2002 |
| publisher | Princeton University Press, |
| record_format | marc |
| series | Princeton series in applied mathematics. |
| series2 | Princeton series in applied mathematics |
| spelling | Embrechts, Paul, 1953- https://id.oclc.org/worldcat/entity/E39PBJdcv8rhpCWw8YwFxGC84q http://id.loc.gov/authorities/names/n97028002 Selfsimilar processes / Paul Embrechts and Makoto Maejima. Princeton, N.J. : Princeton University Press, ©2002. 1 online resource (x, 111 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Princeton series in applied mathematics Includes bibliographical references (pages 101-108) and index. Print version record. 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. 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. In English. Self-similar processes. http://id.loc.gov/authorities/subjects/sh2003001114 Distribution (Probability theory) http://id.loc.gov/authorities/subjects/sh85038545 Processus autosimilaires. Distribution (Théorie des probabilités) distribution (statistics-related concept) aat MATHEMATICS Probability & Statistics Stochastic Processes. bisacsh Distribution (Probability theory) fast Self-similar processes fast Almost surely. Approximation. Asymptotic analysis. Autocorrelation. Autoregressive conditional heteroskedasticity. Autoregressive-moving-average model. Availability. Benoit Mandelbrot. Brownian motion. Central limit theorem. Change of variables. Computational problem. Confidence interval. Correlogram. Covariance matrix. Data analysis. Data set. Determination. Fixed point (mathematics). Foreign exchange market. Fractional Brownian motion. Function (mathematics). Gaussian process. Heavy-tailed distribution. Heuristic method. High frequency. Inference. Infimum and supremum. Instance (computer science). Internet traffic. Joint probability distribution. Likelihood function. Limit (mathematics). Linear regression. Log-log plot. Marginal distribution. Mathematica. Mathematical finance. Mathematics. Methodology. Mixture model. Model selection. Normal distribution. Parametric model. Power law. Probability theory. Publication. Random variable. Regime. Renormalization. Result. Riemann sum. Self-similar process. Self-similarity. Simulation. Smoothness. Spectral density. Square root. Stable distribution. Stable process. Stationary process. Stationary sequence. Statistical inference. Statistical physics. Statistics. Stochastic calculus. Stochastic process. Technology. Telecommunication. Textbook. Theorem. Time series. Variance. Wavelet. Website. Maejima, Makoto. has work: Selfsimilar processes (Text) https://id.oclc.org/worldcat/entity/E39PCGfJ8YwQ7Gc8Wk4t4Wpybd https://id.oclc.org/worldcat/ontology/hasWork Print version: Embrechts, Paul, 1953- Selfsimilar processes. Princeton, N.J. : Princeton University Press, ©2002 0691096279 (DLC) 2002108314 (OCoLC)48837321 Princeton series in applied mathematics. http://id.loc.gov/authorities/names/no2002046464 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=81049 Volltext |
| spellingShingle | Embrechts, Paul, 1953- Selfsimilar processes / Princeton series in applied mathematics. 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. Self-similar processes. http://id.loc.gov/authorities/subjects/sh2003001114 Distribution (Probability theory) http://id.loc.gov/authorities/subjects/sh85038545 Processus autosimilaires. Distribution (Théorie des probabilités) distribution (statistics-related concept) aat MATHEMATICS Probability & Statistics Stochastic Processes. bisacsh Distribution (Probability theory) fast Self-similar processes fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2003001114 http://id.loc.gov/authorities/subjects/sh85038545 |
| title | Selfsimilar processes / |
| title_auth | Selfsimilar processes / |
| title_exact_search | Selfsimilar processes / |
| title_full | Selfsimilar processes / Paul Embrechts and Makoto Maejima. |
| title_fullStr | Selfsimilar processes / Paul Embrechts and Makoto Maejima. |
| title_full_unstemmed | Selfsimilar processes / Paul Embrechts and Makoto Maejima. |
| title_short | Selfsimilar processes / |
| title_sort | selfsimilar processes |
| topic | Self-similar processes. http://id.loc.gov/authorities/subjects/sh2003001114 Distribution (Probability theory) http://id.loc.gov/authorities/subjects/sh85038545 Processus autosimilaires. Distribution (Théorie des probabilités) distribution (statistics-related concept) aat MATHEMATICS Probability & Statistics Stochastic Processes. bisacsh Distribution (Probability theory) fast Self-similar processes fast |
| topic_facet | Self-similar processes. Distribution (Probability theory) Processus autosimilaires. Distribution (Théorie des probabilités) distribution (statistics-related concept) MATHEMATICS Probability & Statistics Stochastic Processes. Self-similar processes |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=81049 |
| work_keys_str_mv | AT embrechtspaul selfsimilarprocesses AT maejimamakoto selfsimilarprocesses |