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Stochastic simulation and Monte Carlo methods : mathematical foundations of stochastic simulation

Author: C Graham; D Talay
Publisher: Berlin ; New York : Springer, ©2013.
Series: Stochastic modelling and applied probability, 68.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners' aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: C Graham; D Talay
ISBN: 9783642393631 3642393632 3642393624 9783642393624
OCLC Number: 854557983
Description: 1 online resource.
Contents: Part I:Principles of Monte Carlo Methods --
1. Introduction --
2. Strong Law of Large Numbers and Monte Carlo Methods --
3. Non Asymptotic Error Estimates for Monte Carlo Methods --
Part II:Exact and Approximate Simulation of Markov Processes --
4. Poisson Processes --
5. Discrete-Space Markov Processes --
6. Continuous-Space Markov Processes with Jumps --
7. Discretization of Stochastic Differential Equations --
Part III:Variance Reduction, Girsanov's Theorem, and Stochastic Algorithms --
8. Variance Reduction and Stochastic Differential Equations --
9. Stochastic Algorithms --
References --
Index.
Series Title: Stochastic modelling and applied probability, 68.
Responsibility: Carl Graham, Denis Talay.

Abstract:

The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte  Read more...

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