Buch, Englisch, 404 Seiten, Previously published in hardcover, Format (B × H): 178 mm x 235 mm, Gewicht: 734 g
Reihe: Springer Series in Operations Research and Financial Engineering
Probabilistic and Statistical Modeling
Buch, Englisch, 404 Seiten, Previously published in hardcover, Format (B × H): 178 mm x 235 mm, Gewicht: 734 g
Reihe: Springer Series in Operations Research and Financial Engineering
ISBN: 978-1-4419-2024-9
Verlag: Springer
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
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Elementare Stochastik
- Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
- Mathematik | Informatik Mathematik Operations Research Spieltheorie
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
Weitere Infos & Material
Crash Courses.- Crash Course I: Regular Variation.- Crash Course II: Weak Convergence; Implications for Heavy-Tail Analysis.- Statistics.- Dipping a Toe in the Statistical Water.- Probability.- The Poisson Process.- Multivariate Regular Variation and the Poisson Transform.- Weak Convergence and the Poisson Process.- Applied Probability Models and Heavy Tails.- More Statistics.- Additional Statistics Topics.- Appendices.- Notation and Conventions.- Software.
