Skip to content

Online ordering will be unavailable on Saturday 10 December 2022, 0800-1800 GMT.

To place an order, please contact Customer Services.

UK/ROW +44 (0) 1223 326050 | US 1 800 872 7423 or 1 212 337 5000 | Australia/New Zealand 61 3 86711400 or 1800 005 210, New Zealand 0800 023 520

Register Sign in Wishlist
Taylor Approximations for Stochastic Partial Differential Equations

Taylor Approximations for Stochastic Partial Differential Equations


Part of CBMS-NSF Regional Conference Series in Applied Mathematics

  • Date Published: December 2011
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial null Mathematics for availability.
  • format: Paperback
  • isbn: 9781611972009


Add to wishlist

Looking for an inspection copy?

This title is not currently available on inspection

Product filter button
About the Authors
  • This book presents a systematic theory of Taylor expansions of evolutionary-type stochastic partial differential equations (SPDEs). The authors show how Taylor expansions can be used to derive higher order numerical methods for SPDEs, with a focus on pathwise and strong convergence. In the case of multiplicative noise, the driving noise process is assumed to be a cylindrical Wiener process, while in the case of additive noise the SPDE is assumed to be driven by an arbitrary stochastic process with Hölder continuous sample paths. Recent developments on numerical methods for random and stochastic ordinary differential equations are also included since these are relevant for solving spatially discretised SPDEs as well as of interest in their own right. The authors include the proof of an existence and uniqueness theorem under general assumptions on the coefficients as well as regularity estimates in an appendix.

    • Provides the reader with access to a rapidly developing field that will be widely applied in future years
    • A rich source of information for those interested in using and further developing numerical methods for stochastic partial differential equations
    • Suitable as source material for graduate courses
    Read more

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity


    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?


    Product details

    • Date Published: December 2011
    • format: Paperback
    • isbn: 9781611972009
    • length: 235 pages
    • dimensions: 250 x 172 x 13 mm
    • weight: 0.39kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial null Mathematics for availability.
  • Table of Contents

    List of figures
    1. Introduction
    Part I. Random and Stochastic Ordinary Partial Differential Equations:
    2. RODEs
    3. SODEs
    4. SODEs with nonstandard assumptions
    Part II. Stochastic Partial Differential Equations:
    5. SPDEs
    6. Numerical methods for SPDEs
    7. Taylor approximations for SPDEs with additive noise
    8. Taylor approximations for SPDEs with multiplicative noise
    Appendix: regularity estimates for SPDEs

  • Authors

    Arnulf Jentzen, Princeton University, New Jersey
    Arnulf Jentzen is appointed as a Visiting Fellow in the Department of Applied and Computational Mathematics at Princeton University. His research focuses on analytical and numerical aspects of stochastic differential equations with non-globally Lipschitz continuous nonlinearities.

    Peter Kloeden, Goethe-Universität Frankfurt am Main
    Peter E. Kloeden is a Professor of Applied and Instrumental Mathematics at Goethe University, Frankfurt am Main. He is a Fellow both of SIAM and of the Australian Mathematical Society. He was awarded the W. T. and Idalia Reid Prize in Mathematics by SIAM in 2006 for his fundamental contributions to the theoretical and computational analysis of differential equations.

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×
warning icon

Turn stock notifications on?

You must be signed in to your Cambridge account to turn product stock notifications on or off.

Sign in Create a Cambridge account arrow icon

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.


Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

Please fill in the required fields in your feedback submission.