Zum Hauptinhalt springen
Nicht aus der Schweiz? Besuchen Sie lehmanns.de
Quasi-Stationary Phenomena in Nonlinearly Perturbed Stochastic Systems - Mats Gyllenberg, Dmitrii S. Silvestrov

Quasi-Stationary Phenomena in Nonlinearly Perturbed Stochastic Systems

Media-Kombination
XII, 579 Seiten | Ausstattung: eBook & Hardcover
2008
De Gruyter
9783119162784 (ISBN)
CHF 359,95 inkl. MwSt
  • Titel leider nicht mehr lieferbar
  • Artikel merken
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.

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

Reihe/Serie De Gruyter Expositions in Mathematics ; 44
Zusatzinfo Includes a print version and an ebook
Verlagsort Berlin/Boston
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik Allgemeines / Lexika
Schlagworte Markov Chains. • Markowscher Prozess • Nonlinearly Perturbed Regenerative Processes • renewal equation • Renewal Equation; Nonlinearly Perturbed Regenerative Processes; Semi-Markov Processes; Markov Chains. • semi-Markov processes • Stochastischer Prozess
ISBN-13 9783119162784 / 9783119162784
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
Haben Sie eine Frage zum Produkt?