Stochastic Simulation and Monte Carlo Methods

Name: Stochastic Simulation and Monte Carlo Methods
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642393624
Price: 26345 HUF
Availability: InStock

Szerző: Carl Graham, Denis Talay

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Elérhetőség: Beszállítói készleten

Küldés 10-13 napon belül

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In various scientific and industrial fields stochastic simulations are taking on a new importance. T...

Információk a könyvről

Szerző

Carl Graham, Denis Talay

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2013

oldal

260

EAN

9783642393624

ISBN

3642393624

Enbook ID

01663997

Kiadó

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Súly

564

Méretek

160 x 243 x 20

Teljes leírás

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 quite complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As result the present volume is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors introduce fundamental notions in stochastic calculus and continuous-time martingale theory; and develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals, and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. 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 Carlo simulations of stochastic processes.The book is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations who will benefit from the ability to reliably estimate and control the accuracy of their simulations.

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Stochastic Simulation and Monte Carlo Methods

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