Skip to main content Accessibility help
×
  • Cited by 58
    • Show more authors
    • You may already have access via personal or institutional login
    • Select format
    • Publisher:
      Cambridge University Press
      Publication date:
      October 2009
      August 2005
      ISBN:
      9780511610547
      9780521844727
      9781107630734
      Dimensions:
      (253 x 177 mm)
      Weight & Pages:
      1.075kg, 528 Pages
      Dimensions:
      (253 x 177 mm)
      Weight & Pages:
      0.84kg, 528 Pages
    You may already have access via personal or institutional login
  • Selected: Digital
    Add to cart View cart Buy from Cambridge.org

    Book description

    This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.

    Reviews

    ‘The text contains a wealth of interesting and useful material, most of which does not work its way into standard first courses in probability or mathematical statistics.'

    Fred Huffer Source: Journal of the American Statistical Association

    ‘The most outstanding aspect of Elements of Distribution Theory is that it solidly fills a gap as an introductory coverage of approximation theory for probability distributions that gracefully avoids measure theory … Severini's proofs are clear, abundant, and illustrate the main techniques.'

    Source: SIAM Review

    ‘A powerful introduction to distribution theory … The book's material is invaluable and has a good presentation … meets its goal and [serves] all who are interested in statistics, and so it is strongly recommended to libraries.'

    Hassan S. Bakouch Source: Journal of the Royal Statistical Society

    ‘The exposition is clear and solving the wide variety of exercises at the end of every chapter will be of help in understanding the subject better. Students wishing to learn distribution theory quickly without the use of measure theory will welcome this book.'

    Sreenivasan Ravi Source: Mathematical Reviews

    'This is a very good book on statistical distribution theory.'

    Source: Zentralblatt MATH

    '… a useful reference with many elegant proofs.'

    David J. Olive Source: Technometrics

    Refine List

    Actions for selected content:

    Select all | Deselect all
    • View selected items
    • Export citations
    • Download PDF (zip)
    • Save to Kindle
    • Save to Dropbox
    • Save to Google Drive

    Save Search

    You can save your searches here and later view and run them again in "My saved searches".

    Please provide a title, maximum of 40 characters.
    ×

    Contents

    Metrics

    Altmetric attention score

    Full text views

    Total number of HTML views: 0
    Total number of PDF views: 0 *
    Loading metrics...

    Book summary page views

    Total views: 0 *
    Loading metrics...

    * Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

    Usage data cannot currently be displayed.

    Accessibility standard: Unknown

    Why this information is here

    This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

    Accessibility Information

    Accessibility compliance for the PDF of this book is currently unknown and may be updated in the future.