Numerical methods for Stochastic differential equations: two examples

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Numerical Methods for Stochastic Differential Equations

Approximately a quarter century ago, very early in my career when I was publishing rather theoretical results about stochastic differential equations, I received a letter (this predates e-mail) from a fellow researcher who had seen my work and was asking if I had an algorithm suitable for implementing my ideas on a computing machine. Not only did I not have such an algorithm, the idea had not o...

متن کامل

Numerical Methods for Stochastic Differential Equations

Stochastic differential equations (SDE's) play an important role in physics but existing numerical methods for solving such equations are of low accuracy and poor stability. A general strategy for developing accurate and efficient schemes for solving stochastic equations is outlined here. High-order numerical methods are developed for the integration of stochastic differential equations with st...

متن کامل

An introduction to numerical methods for stochastic differential equations

This paper aims to give an overview and summary of numerical methods for the solution of stochastic differential equations. It covers discrete time strong and weak approximation methods that are suitable for different applications. A range of approaches and results is discussed within a unified framework. On the one hand, these methods can be interpreted as generalizing the welldeveloped theory...

متن کامل

Numerical methods for stochastic partial differential equations with multiples scales

Article history: Received 23 May 2011 Received in revised form 3 October 2011 Accepted 27 November 2011 Available online 13 December 2011

متن کامل

Numerical methods for nonlinear stochastic differential equations with jumps

We present and analyse two implicit methods for Ito stochastic differential equations (SDEs) with Poisson-driven jumps. The first method, SSBE, is a split-step extension of the backward Euler method. The second method, CSSBE, arises from the introduction of a compensated, martingale, form of the Poisson process. We show that both methods are amenable to rigorous analysis when a one-sided Lipsch...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: ESAIM: Proceedings and Surveys

سال: 2018

ISSN: 2267-3059

DOI: 10.1051/proc/201864065