Random Sums and Branching Stochastic Processes

Ibrahim Rahimov

ISBN 10: 038794446X / ISBN 13: 9780387944463

Verlag: Springer New York, Springer US Jan 1995, 1995

Beschreibung

Neuware -The aim of this monograph is to show how random sums (that is, the summation of a random number of dependent random variables) may be used to analyse the behaviour of branching stochastic processes. The author shows how these techniques may yield insight and new results when applied to a wide range of branching processes. In particular, processes with reproduction-dependent and non-stationary immigration may be analysed quite simply from this perspective. On the other hand some new characterizations of the branching process without immigration dealing with its genealogical tree can be studied. Readers are assumed to have a firm grounding in probability and stochastic processes, but otherwise this account is self-contained. As a result, researchers and graduate students tackling problems in this area will find this makes a useful contribution to their work.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 212 pp. Englisch.

Bestandsnummer des Verkäufers 9780387944463

Bibliografische Details

• Titel: Random Sums and Branching Stochastic Processes
• Verlag: Springer New York, Springer US Jan 1995
• Erscheinungsjahr: 1995
• Sprache: Englisch
• ISBN-10: 038794446X
• ISBN-13: 9780387944463
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

The aim of this monograph is to show how random sums (that is, the summation of a random number of dependent random variables) may be used to analyse the behaviour of branching stochastic processes. The author shows how these techniques may yield insight and new results when applied to a wide range of branching processes. In particular, processes with reproduction-dependent and non-stationary immigration may be analysed quite simply from this perspective. On the other hand some new characterizations of the branching process without immigration dealing with its genealogical tree can be studied. Readers are assumed to have a firm grounding in probability and stochastic processes, but otherwise this account is self-contained. As a result, researchers and graduate students tackling problems in this area will find this makes a useful contribution to their work.