Asymptotic Analysis of Random Walks: Heavy-Tailed Distributions - Encyclopedia of Mathematics and Its Applications 118 (Hardback)
  • Asymptotic Analysis of Random Walks: Heavy-Tailed Distributions - Encyclopedia of Mathematics and Its Applications 118 (Hardback)
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Asymptotic Analysis of Random Walks: Heavy-Tailed Distributions - Encyclopedia of Mathematics and Its Applications 118 (Hardback)

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£149.00
Hardback 656 Pages / Published: 12/06/2008
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This book focuses on the asymptotic behaviour of the probabilities of large deviations of the trajectories of random walks with 'heavy-tailed' (in particular, regularly varying, sub- and semiexponential) jump distributions. Large deviation probabilities are of great interest in numerous applied areas, typical examples being ruin probabilities in risk theory, error probabilities in mathematical statistics, and buffer-overflow probabilities in queueing theory. The classical large deviation theory, developed for distributions decaying exponentially fast (or even faster) at infinity, mostly uses analytical methods. If the fast decay condition fails, which is the case in many important applied problems, then direct probabilistic methods usually prove to be efficient. This monograph presents a unified and systematic exposition of the large deviation theory for heavy-tailed random walks. Most of the results presented in the book are appearing in a monograph for the first time. Many of them were obtained by the authors.

Publisher: Cambridge University Press
ISBN: 9780521881173
Number of pages: 656
Weight: 1220 g
Dimensions: 234 x 156 x 40 mm


MEDIA REVIEWS
'This book is a worthy tribute to the amazing fecundity of the structure of random walks!' Mathematical Reviews
'... an up-to-date, unified and systematic exposition of the field. Most of the results presented are appearing in a monograph for the first time and a good proportion of them were obtained by the authors. ... The book presents some beautiful and useful mathematics that may attract a number of probabilists to the large deviations topic in probability.' EMS Newsletter

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