Skip to content
Cart

Your Cart

×

You have 0 items in your cart.

Register Sign in Wishlist

Optimal Estimation of Parameters

$144.00 (C)

  • Date Published: July 2012
  • availability: In stock
  • format: Hardback
  • isbn: 9781107004740

$ 144.00 (C)
Hardback

Add to cart Add to wishlist

Other available formats:
eBook


Looking for an examination copy?

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 presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a generalized maximum capacity estimator. This approach allows the optimal estimation of real-valued parameters, their number and intervals, as well as providing common ground for explaining the power of these estimators. Beginning with a review of coding and the key properties of information, the author goes on to discuss the techniques of estimation and develops the generalized maximum capacity estimator, based on a new form of Shannon's mutual information and channel capacity. Applications of this powerful technique in hypothesis testing and denoising are described in detail. Offering an original and thought-provoking perspective on estimation theory, Jorma Rissanen's book is of interest to graduate students and researchers in the fields of information theory, probability and statistics, econometrics and finance.

    • Describes a powerful new tool, the generalized maximum likelihood estimator
    • Sets out an original and thought-provoking perspective on estimation theory
    • Describes the only denoising algorithm where 'noise' is defined, as the part in the data that cannot be compressed by the Gaussian model class selected
    Read more

    Reviews & endorsements

    "The minimum description length (MDL) principle is a very universal principle of statistical modeling in estimation, prediction, testing, and coding. Jorma Rissanen, the pioneer of the MDL principle, evolves a new theory to reach the most general and complete notion, which he calls the complete MDL principle. In this book the author derives it by introducing the key notion of maximum capacity. The most fundamental methods of estimation such as maximum likelihood estimation and the MDL estimation are naturally derived as the maximum capacity estimators, and their optimality is justified within a unifying theoretical framework. Through the book, readers can revisit the meaning of estimation from the author's very original viewpoint, and will enjoy the most advanced version of the MDL principle." - Kenji Yamanishi, The University of Tokyo

    "In this splendid new book, Jorma Rissanen, the originator of the minimum description length (MDL) Principle, puts forward a comprehensive theory of estimation which differs in several ways from the standard Bayesian and frequentist approaches. During the development of MDL over the last 30 years, it gradually emerged that MDL could be viewed, informally, as a maximum probability principle that directly extends Fisher's classical maximum likelihood method to allow for estimation of a model's structural properties. Yet providing a formal link between MDL and maximum probability remained elusive until the arrival of this book. By making the connection mathematically precise, Rissanen now ties up the loose ends of MDL theory and at the same time develops a beautiful, unified, entirely original and fully coherent theory of estimation, which includes hypothesis testing as a special case." - Peter GrĂĽnwald, Centrum voor Wiskunde en Informatica, The Netherlands

    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: July 2012
    • format: Hardback
    • isbn: 9781107004740
    • length: 170 pages
    • dimensions: 254 x 178 x 12 mm
    • weight: 0.51kg
    • contains: 8 b/w illus. 3 tables
    • availability: In stock
  • Table of Contents

    1. Introduction
    2. Coding
    3. Basics of information
    4. Modeling problem
    5. Other optimality properties
    6. Interval estimation
    7. Hypothesis testing
    8. Denoising
    9. Sequential models
    Appendix A. Elements of algorithmic information
    Appendix B. Universal prior for integers.

  • Author

    Jorma Rissanen, Tampere University of Technology, Finland
    Jorma Rissanen was a member of research staff in IBM Almaden Research Center from 1965 to 2001 and is currently Professor Emeritus at Technical University of Tampere, Finland. Among his main achievements are the introduction of the MDL principle for statistics, the invention of arithmetic coding and the introduction of variable-length Markov chains with the associated Algorithm Context. He has received many awards, including the 2007 Kolmogorov medal from the CLRC, University of London, and the 2009 Shannon Award from the Information Theory Society. He received two Outstanding Innovation Awards from IBM in 1980 and 1988 and a Corporate Award in 1991.

Sign In

Please sign in to access your account

Cancel

Not already registered? Create an account now. ×

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 ×

Find content that relates to you

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.
×