Asymptotic Analysis of Random Walks

Asymptotic Analysis of Random Walks : Heavy-tailed Distributions

By (author) A. A. Borovkov , By (author) K. A. Borovkov

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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.

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  • Hardback | 656 pages
  • 160 x 240 x 52mm | 1,220.16g
  • 30 Jun 2008
  • CAMBRIDGE UNIVERSITY PRESS
  • Cambridge
  • English
  • New.
  • 5 b/w illus.
  • 052188117X
  • 9780521881173
  • 1,681,554

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Author Information

Alexander Borovkov works at the Sobolev Institute of Mathematics in Novosibirsk. Konstantin Borovkov is a staff member in the Department of Mathematics and Statistics at the University of Melbourne.

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Review quote

'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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