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
place on personal bookshelves of many applied probabilists." (Ilya S. Molchanov, Mathematical Reviews, Issue 2008 j)
"'This is a survey of the mathematical, probabilistic and statistical tools used in heavy-tail analysis as well as some examples of their use.' ? This book could be used very conveniently for a Masters-level course in point processes or regular variation; theoretical concepts are introduced in a pedagogical way, and several exercises accompany each chapter. Researchers in applied probability or statistics will also benefit from reading this book. It cleverly mixes probabilistic modeling and statistical methodology with powerful mathematical tools." (Anne-Laure Fougéres and Philippe Soulier, SIAM Review, Vol. 50 (2), 2008)
"This book does the job of presenting the general problematic and providing tools for solving the study of the related models, successfully. ? Altogether the book has 11 chapters and a series of illustrative examples coming from real life, which are discussed, and a list of exercises are proposed in each chapter. The book will certainly be useful for mathematicians, engineers, economists, and other specialists coping with heavy-tailed problems." (C. Bouza, Journal of the Operational Research Society, Vol. 61 (12), 2010)
