Fr. 266.00

Quasi-Stationary Phenomena in Nonlinearly Perturbed Stochastic Systems

English · Hardback

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Description

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The book is devoted to studies of quasi-stationary phenomena in nonlinearly perturbed stochastic systems. New methods of asymptotic analysis for nonlinearly perturbed stochastic processes based on new types of asymptotic expansions for perturbed renewal equation and recurrence algorithms for construction of asymptotic expansions for Markov type processes with absorption are presented. Asymptotic expansions are given in mixed ergodic (for processes) and large deviation theorems (for absorption times) for nonlinearly perturbed regenerative processes, semi-Markov processes, and Markov chains. Applications to analysis of quasi-stationary phenomena in nonlinearly perturbed queueing systems, population dynamics and epidemic models, and for risk processes are presented. The book also contains an extended bibliography of works in the area. It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications and may be also useful for doctoral and advanced undergraduate students.

About the author










Mats Gyllenberg, University of Helsinki, Finland; Dmitrii S. Silvestrov, Mälardalen University, Sweden.

Report

"Besides of an original material the book contains a reach reference information on processes what a dealt with, and also a wide bibliography (1094 items) on affected theme."B. P. Harlamow in: Zentralblatt Math 1/2010 "It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications that will contribute to the continuing extensive studies in the area and remain relevant für years to come."In: Enseignement Mathematique 2/2009

Product details

Authors Mat Gyllenberg, Mats Gyllenberg, Dmitrii S Silvestrov, Dmitrii S. Silvestrov
Publisher De Gruyter
 
Languages English
Product format Hardback
Released 22.09.2008
 
EAN 9783110204377
ISBN 978-3-11-020437-7
No. of pages 579
Dimensions 170 mm x 43 mm x 240 mm
Weight 1102 g
Series De Gruyter Expositions in Mathematics
Gruyter Expositions in Mathematics
De Gruyter Expositions in Mathematics
ISSN
Subject Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics

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