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An Introduction to Heavy-Tailed and Subexponential Distributions

An Introduction to Heavy-Tailed and Subexponential Distributions
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Field name Details
Dewey Class 519.2
Title An Introduction to Heavy-Tailed and Subexponential Distributions (EB) / by Sergey Foss, Dmitry Korshunov, Stan Zachary.
Author Foss, Sergey
Added Personal Name Korshunov, Dmitry
Zachary, Stan
Other name(s) SpringerLink (Online service)
Edition statement 2nd ed. 2013.
Publication New York, NY : Springer
, 2013.
Physical Details XI, 157 pages. 2 illus. : online resource.
Series Springer Series in Operations Research and Financial Engineering 1431-8598
ISBN 9781461471011
Summary Note 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.:
Contents note Preface -- Introduction -- Heavy- and long-tailed distributions -- Subexponential distributions -- Densities and local probabilities -- Maximum of random walks -- References -- Index.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site http://dx.doi.org/10.1007/978-1-4614-7101-1
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