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 directcs@cambridge.org +44 (0) 1223 326050 | US customer_service@cambridge.org 1 800 872 7423 or 1 212 337 5000 | Australia/New Zealand enquiries@cambridge.edu.au 61 3 86711400 or 1800 005 210, New Zealand 0800 023 520

Register Sign in Wishlist
A User's Guide to Measure Theoretic Probability

A User's Guide to Measure Theoretic Probability

$54.99 (P)

Part of Cambridge Series in Statistical and Probabilistic Mathematics

  • Date Published: December 2001
  • availability: Available
  • format: Paperback
  • isbn: 9780521002899

Paperback

Add to wishlist

Other available formats:
Hardback, eBook


Looking for an examination copy?

This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • This book grew from a one-semester course offered for many years to a mixed audience of graduate and undergraduate students who have not had the luxury of taking a course in measure theory. The core of the book covers the basic topics of independence, conditioning, martingales, convergence in distribution, and Fourier transforms. In addition there are numerous sections treating topics traditionally thought of as more advanced, such as coupling and the KMT strong approximation, option pricing via the equivalent martingale measure, and the isoperimetric inequality for Gaussian processes. The book is not just a presentation of mathematical theory, but is also a discussion of why that theory takes its current form. It will be a secure starting point for anyone who needs to invoke rigorous probabilistic arguments and understand what they mean.

    • Numerous exercises
    • Contains many comments, explanations and aids to intuition, not just wall-to-wall mathematics
    • Unusual treatment of advanced topics, using streamlined notation and methods accessible to students who have not studied probability at this level before
    Read more

    Reviews & endorsements

    "Unlike technical books of a previous generation, here we have an author admitting that a reader might find the subject difficult and even offering a window on the pedagogical considerations by which he shapes his exposition. Pollard does not just explain and clarify abstractions; he really sells them to a presumably skeptical reader. Thus he bridges a gap in the literature, between elementary probability texts and advanced works that presume a secure prior knowledge of measure theory...The nice layout and occasional useful diagram further amplify the friendliness of this book." Choice

    "The book ... can be recommended as an excellent source in measuring theoretic probability theory as well as a handbook for everybody who studies stochastic processes in the real world." Mathematical Reviews

    See more reviews

    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 2001
    • format: Paperback
    • isbn: 9780521002899
    • length: 366 pages
    • dimensions: 255 x 181 x 21 mm
    • weight: 0.64kg
    • contains: 200 exercises
    • availability: Available
  • Table of Contents

    1. Motivation
    2. A modicum of measure theory
    3. Densities and derivatives
    4. Product spaces and independence
    5. Conditioning
    6. Martingale et al
    7. Convergence in distribution
    8. Fourier transforms
    9. Brownian motion
    10. Representations and couplings
    11. Exponential tails and the law of the iterated logarithm
    12. Multivariate normal distributions
    Appendix A. Measures and integrals
    Appendix B. Hilbert spaces
    Appendix C. Convexity
    Appendix D. Binomial and normal distributions
    Appendix E. Martingales in continuous time
    Appendix F. Generalized sequences.

  • Author

    David Pollard, Yale University, Connecticut

Sorry, this resource is locked

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

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 www.ebooks.com. Please see the permission section of the www.ebooks.com 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.

Cancel

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.
×