Sprache: Englisch
Verlag: Cambridge University Press, 2002
ISBN 10: 0521811295 ISBN 13: 9780521811293
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 196,39
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Cambridge University Press, 2002
ISBN 10: 0521811295 ISBN 13: 9780521811293
Anbieter: Kennys Bookstore, Olney, MD, USA
EUR 283,68
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. The complete theory of stochastic differential equations driven by jumps, their stability, and numerical approximation theories. Series: Encyclopedia of Mathematics and Its Applications. Num Pages: 516 pages, 17 b/w illus. 1 table 745 exercises. BIC Classification: PBK. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 29. Weight in Grams: 897. . 2002. Illustrated. hardcover. . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Cambridge University Press, 2002
ISBN 10: 0521811295 ISBN 13: 9780521811293
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Stochastic processes with jumps and random measures are importance as drivers in applications like financial mathematics and signal processing. This 2002 text develops stochastic integration theory for both integrators (semimartingales) and random measures from a common point of view. Using some novel predictable controlling devices, the author furnishes the theory of stochastic differential equations driven by them, as well as their stability and numerical approximation theories. Highlights feature DCT and Egoroff's Theorem, as well as comprehensive analogs results from ordinary integration theory, for instance previsible envelopes and an algorithm computing stochastic integrals of càglàd integrands pathwise. Full proofs are given for all results, and motivation is stressed throughout. A large appendix contains most of the analysis that readers will need as a prerequisite. This will be an invaluable reference for graduate students and researchers in mathematics, physics, electrical engineering and finance who need to use stochastic differential equations.