Skip to content
Register Sign in Wishlist

Statistical Modelling by Exponential Families

$39.99 (P)

Part of Institute of Mathematical Statistics Textbooks

  • Date Published: October 2019
  • availability: In stock
  • format: Paperback
  • isbn: 9781108701112

$ 39.99 (P)

Add to cart 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 providing details of the course you are teaching.

Product filter button
About the Authors
  • This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful distributions in statistical theory, including the normal, gamma, binomial, Poisson, and negative binomial. Strongly motivated by applications, it presents the essential theory and then demonstrates the theory's practical potential by connecting it with developments in areas like item response analysis, social network models, conditional independence and latent variable structures, and point process models. Extensions to incomplete data models and generalized linear models are also included. In addition, the author gives a concise account of the philosophy of Per Martin-Löf in order to connect statistical modelling with ideas in statistical physics, including Boltzmann's law. Written for graduate students and researchers with a background in basic statistical inference, the book includes a vast set of examples demonstrating models for applications and exercises embedded within the text as well as at the ends of chapters.

    • Expands and extends the theory and application of exponential families within one concise volume
    • Uses recurrent themes in examples and exercises to build familiarity with the models
    • Gives a concise account of the philosophy of Per Martin-Löf, connecting statistical modelling with ideas in statistical physics
    Read more

    Reviews & endorsements

    'Rolf Sundberg’s book gives attractive properties of the exponential family and illustrates them for a wide variety of applications. Definitions are concise and most propositions look directly appealing. The writing reflects the author’s experience in deriving results that are essential for good modelling and convincing inference. Thus, this book is indispensable for all data scientists, be they graduate students or experienced researchers.' Nanny Wermuth, Chalmers tekniska högskola, Sweden

    ‘This is an excellent book on exponential families. It covers not only the basic properties of exponential families but also several modern topics such as graphical models and random networks. The author blends theories and applications elegantly and provides several useful examples from various scientific domains. It is suitable for a one-semester graduate-level course and will be an excellent reference for topic courses such as stochastic modeling and parametric models.’ Yen-Chi Chen, Journal of the American Statistical Association

    ‘Overall, this is a clearly written, graduate-level introduction to an important area of statistical modelling. The numerous examples and exercises included throughout provide invaluable illustrations across a number of application areas, making this a useful reference for both researchers and practitioners. As a textbook, it is an excellent starting point for either a taught course on statistical inference with an emphasis on data from the exponential family, or for self-directed study in this area.’ Fraser Daly, Institute of Mathematical Statistics Textbooks

    ‘This book is perfect for an introductory theoretical graduate course but its parts could also definitely be used in a more applied course. The only prerequisite is basic mathematical statistics. The book is also very handy as a general reference on exponential families. To keep the content simple, the author sometimes avoids the most technical details; however, all necessary references are provided for the reader’s convenience. In this sense the book can be used by any researcher interested in exponential families from either a more theoretical or more applied point of view.’ Piotr Zwiernik, MathSciNet

    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: October 2019
    • format: Paperback
    • isbn: 9781108701112
    • length: 296 pages
    • dimensions: 228 x 152 x 17 mm
    • weight: 0.43kg
    • contains: 22 b/w illus. 100 exercises
    • availability: In stock
  • Table of Contents

    1. What is an exponential family?
    2. Examples of exponential families
    3. Regularity conditions and basic properties
    4. Asymptotic properties of the MLE
    5. Testing model-reducing hypotheses
    6. Boltzmann's law in statistics
    7. Curved exponential families
    8. Extension to incomplete data
    9. Generalized linear models
    10. Graphical models for conditional independence structures
    11. Exponential family models for social networks
    12. Rasch models for item response and related models
    13. Models for processes in space or time
    14. More modelling exercises
    Appendix A. Statistical concepts and principles
    Appendix B. Useful mathematics.

  • Resources for

    Statistical Modelling by Exponential Families

    Rolf Sundberg

    General Resources

    Find resources associated with this title

    Type Name Unlocked * Format Size

    Showing of

    Back to top

    This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to instructors whose faculty status has been verified. To gain access to locked resources, instructors should sign in to or register for a Cambridge user account.

    Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other instructors may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

    Supplementary resources are subject to copyright. Instructors are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.

    If you are having problems accessing these resources please contact

  • Author

    Rolf Sundberg, Stockholms Universitet
    Rolf Sundberg is Professor Emeritus of Statistical Science at Stockholms Universitet. His work embraces both theoretical and applied statistics, including principles of statistics, exponential families, regression, chemometrics, stereology, survey sampling inference, molecular biology, and paleoclimatology. In 2003, with M. Linder, he won the award for best theoretical paper in the Journal of Chemometrics for their work on multivariate calibration, and in 2017 he was named Statistician of the Year by the Swedish Statistical Society.

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.