Heavy-Tail Phenomena : Probabilistic and Statistical Modeling
This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. Heavy tails are characteristic of phenomena where there is a significant probability of a single huge value impacting system behavior. Record-breaking i...
Αποθηκεύτηκε σε:
| Κύριος συγγραφέας: | |
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| Μορφή: | Livre numérique |
| Γλώσσα: | Anglais |
| Έκδοση: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Έκδοση: | 1st ed. 2007. |
| Σειρά: | Springer Series in Operations Research and Financial Engineering
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| Θέματα: | |
| Διαθέσιμο Online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Σημείωση: |
L'impression du document génère 414 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Heavy-tail phenomena, probabilistic and statistical modeling, Sidney I. Resnick, 2007, New York, Springer, 1 vol. (XIX-404 p.), Springer series in operations research and financial engineering, 978-0-387-24272-9 |
| Περίληψη: | This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. Heavy tails are characteristic of phenomena where there is a significant probability of a single huge value impacting system behavior. Record-breaking insurance losses, financial returns, sizes of files stored on a server, transmission rates of files are all examples of heavy-tailed phenomena. Key features: Unique text devoted to heavy-tails. The treatment of heavy tails is largely dimensionless. The text gives attention to both probability modeling and statistical methods for fitting models. Most other books focus on one or the other but not both. The book emphasizes the broad applicability of heavy-tails to the fields of finance (e.g., value-at- risk), data networks, insurance. The presentation is clear, efficient and coherent and, balances theory and data analysis to show the applicability and limitations of certain methods. Several chapters examine in detail the mathematical properties of the methodologies as well as their implementation in the Splus or R statistical languages. The exposition is driven by numerous examples and exercises. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use (or at least to learn) a statistics package such as R or Splus. This work will serve second-year graduate students and researchers in the areas of operations research, statistics, applied mathematics, electrical engineering, financial engineering, networking and economics. Sidney Resnick is a Professor at Cornell University and has written several well-known bestsellers: A Probability Path (ISBN: 081764055X), Adventures in Stochastic Processes (ISBN: 0817635912) and Extreme Values, Regular Variation, and Point Processes (ISBN: 0387964819) |
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| Περιγραφή τεκμηρίου: | L'impression du document génère 414 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Βιβλιογραφία: | Bibliogr. Index |
| ISBN: | 9780387450247 |
| ISSN: | 2197-1773 |
| Πρόσβαση: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |