Heavy-tail phenomena : probabilistic and statistical modeling
Author(s)
Bibliographic Information
Heavy-tail phenomena : probabilistic and statistical modeling
（Springer series in operations research and financial engineering）
Springer, c2007
- : pbk
Available at 21 libraries
Note
Includes bibliographical references (p. [377]-396) and index
Description and Table of Contents
Description
This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. It is uniquely devoted to heavy-tails and emphasizes both probability modeling and statistical methods for fitting models.
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 a statistics package. This work will serve second-year graduate students and researchers in the areas of applied mathematics, statistics, operations research, electrical engineering, and economics.
Table of Contents
- 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.
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