Although visible, major advances have been made in the last decade, heavy-tailed distributions and processes have long been studied by probabilists and mathematical statisticians. Aimed at the general practitioner, A Practical Guide to Heavy Tails, is a unique collection of essays that is concerned primarily with a large number of techniques and approaches for data analysis.

The expository papers, all by distinguished experts, are intended for a wide audience from different disciplines. Thus, the papers run the gamut of applications of heavy-tailed modeling, e.g., telecommunications, the Web, insurance, finance. Along with specific applications are several papers devoted to time series analysis, regression, classical signal/noise detection problems, and the general structure of stable processes, viewed from a modeling standpoint.

Considerable emphasis is placed on recent developments in handling the numerical problems associated with stable distributions, which, until recently, have been one of the main technical difficulties in working in the heavy-tailed setting.

Although the emphasis of the book is on applicability rather than theory, many of the questions posed in the individual papers require heavy theoretical analysis to be fully answered; therefore, the book will provide a good source of problems for theoreticians as well.

Table of Contents (in Postcript), (in Acrobat format)