عنوان

Stochastic Simulation and Monte Carlo Method

شابک

9783642393631

کد کشور

IR

شماره

EN-52312

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

کشور محل نشر

IR

عنوان اصلي

Stochastic Simulation and Monte Carlo Method

نام عام مواد

[Book]

ساير اطلاعات عنواني

:Mathematical Foundations of Stochastic Simulation

نام نخستين پديدآور

/ by Carl Graham, Denis Talay

محل نشرو پخش و غیره

Berlin, Heidelberg

نام ناشر، پخش کننده و غيره

: Springer Berlin Heidelberg :Imprint: Springer,

تاریخ نشرو بخش و غیره

, 2013.

نام خاص و کميت اثر

XVI, 260 p. 4 illus., online resource.

عنوان فروست

(Stochastic Modelling and Applied Probability,0172-4568

مشخصه جلد

; 68)

متن يادداشت

Electronic

متن يادداشت

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 highly 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 a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of It?لإ 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. It 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.

متن يادداشت

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.?╗╣

عنوان

Stochastic Modelling and Applied Probability,0172-4568

شماره جلد

68

موضوع مستند نشده

Mathematics

موضوع مستند نشده

Finance

موضوع مستند نشده

Numerical analysis

موضوع مستند نشده

Distribution (Probability theory)

موضوع مستند نشده

Electronic books

شماره رده

مستند نام اشخاص تاييد نشده

Graham, Carl.

مستند نام اشخاص تاييد نشده

Talay, Denis

مستند نام اشخاص تاييد نشده

SpringerLink (Online service)

کشور

ایران

نام ميزبان

9783642393624.pdf

شماره دسترسي

عادی

اطلاعات مختصر

عادی

تاريخ و ساعت مذاکره و دسترسي

9783642393624.pdf

نوع فرمت الکترونيکي

متن

وضعیت فهرست نویسی

old catalog

فرمت انتشار

e

نوع ماده

BL

پیشوند ISBD اعمال شده است

1

سطح دسترسي

a

تكميل شده

Y