Numerical solution of SDE through computer experiments.

Kloeden, Peter E., Eckhard Platen and Henri Schurz:

ISBN 10: 3540570748 / ISBN 13: 9783540570745

Editore: Berlin ; Heidelberg ; Singapore ; Tokyo ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Santa Clara : Springer, 2003

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XIV,292 Seiten. FRISCHES, SEHR schönes Exemplar der VERBESSERTEN Auflage. - In EXCELLENT shape. ( We offer a lot of books on PHYSICS and MATHEMATICS on stock in EXCELLENT shape). Sprache: Englisch Gewicht in Gramm: 505.

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Dati bibliografici

• Titolo: Numerical solution of SDE through computer experiments.
• Editore: Berlin ; Heidelberg ; Singapore ; Tokyo ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Santa Clara : Springer
• Data di pubblicazione: 2003
• Lingua: Inglese
• ISBN 10: 3540570748
• ISBN 13: 9783540570745
• Edizione: CORRECTED third printing.
• Condizione: Wie neu
• Cataloghi dei venditori:
  • Mathematik

Descrizione articolo

Riassunto

This book provides an easily accessible, computationally-oriented introduction into the numerical solution of stochastic differential equations using computer experiments. It develops in the reader an ability to apply numerical methods solving stochastic differential equations. It also creates an intuitive understanding of the necessary theoretical background. Software containing programs for over 100 problems is available online.

Dalla quarta di copertina

This is a computer experimental introduction to the numerical solution of stochastic differential equations. A downloadable software software containing programs for over 100 problems is provided at one of the following homepages:

http://www.math.uni-frankfurt.de/numerik/kloeden/

http://www.business.uts.edu.au/finance/staff/eckard.html

http://www.math.siu.edu/schurz/SOFTWARE/

to enable the reader to develop an intuitive understanding of the issues involved. Applications include stochastic dynamical systems, filtering, parametric estimation and finance modeling.

The book is intended for readers without specialist stochastic background who want to apply such numerical methods to stochastic differential equations that arise in their own field. It can also be used as an introductory textbook for upper-level undergraduate or graduate students in engineering, physics and economics.