An Introduction to Heavy-Tailed and Subexponential Distributions

  • Sergey Foss
  • Dmitry Korshunov
  • Stan Zachary

Table of contents

  1. Front Matter
    Pages i-xi
  2. Sergey Foss, Dmitry Korshunov, Stan Zachary
    Pages 1-6
  3. Sergey Foss, Dmitry Korshunov, Stan Zachary
    Pages 7-42
  4. Sergey Foss, Dmitry Korshunov, Stan Zachary
    Pages 43-74
  5. Sergey Foss, Dmitry Korshunov, Stan Zachary
    Pages 75-102
  6. Sergey Foss, Dmitry Korshunov, Stan Zachary
    Pages 103-143
  7. Back Matter
    Pages 145-157

About this book

Introduction

Heavy-tailed probability distributions are an important component in the modeling of many stochastic systems. They are frequently used to accurately model inputs and outputs of computer and data networks and service facilities such as call centers. They are an essential for describing risk processes in finance and also for insurance premia pricing, and such distributions occur naturally in models of epidemiological spread. The class includes distributions with power law tails such as the Pareto, as well as the lognormal and certain Weibull distributions.

 

One of the highlights of this new edition is that it includes problems at the end of each chapter. Chapter 5 is also updated to include interesting applications to queueing theory, risk, and branching processes. New results are presented in a simple, coherent and systematic way.

Graduate students as well as modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.

Keywords

environmental modeling financial modeling lognormal distribution long-tailed distribution pareto distribution

Authors and affiliations

  • Sergey Foss
    • 1
  • Dmitry Korshunov
    • 2
  • Stan Zachary
    • 3
  1. 1., Department of Actuarial MathematicsHeriot-Watt UniversityRiccarton, EdinburghUnited Kingdom
  2. 2.Russian Academy of SciencesSobolev Institute of Mathematics of theNovosibirskRussia
  3. 3., Department of Actuarial Mathematics andHeriot-Watt UniversityRiccarton, EdinburghUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-7101-1
  • Copyright Information Springer Science + Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-7100-4
  • Online ISBN 978-1-4614-7101-1
  • Series Print ISSN 1431-8598
  • About this book