Skip to content

Due to scheduled maintenance, if purchasing is normally available on this site, it will not be available from Saturday 18th November 07:00 GMT until Sunday 19th November 15:00 GMT. We apologise for the inconvenience.

Cart

Your Cart

×

You have 0 items in your cart.

Register Sign in Wishlist

Nonparametric Estimation under Shape Constraints
Estimators, Algorithms and Asymptotics

£57.00

Part of Cambridge Series in Statistical and Probabilistic Mathematics

  • Date Published: December 2014
  • availability: In stock
  • format: Hardback
  • isbn: 9780521864015

£ 57.00
Hardback

Add to cart Add to wishlist

Other available formats:
eBook


Looking for an inspection copy?

This title is not currently available on inspection

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an introduction to the subject, while the later chapters are written with graduate students and researchers in mathematical statistics in mind. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature.

    • Contains many exercises (190)
    • Utilizes recent research in the field
    • Covers both mathematical and algorithmic aspects
    Read more

    Reviews & endorsements

    'Shape constraints arise naturally in many statistical applications and are becoming increasingly popular as a means of combining the best of the parametric and nonparametric worlds. This book, written by two experts in the field, gives a detailed treatment of many of their attractive features. I have no doubt it will be a valuable resource for researchers, students, and others interested in learning about this fascinating area.' Richard Samworth, University of Cambridge

    'I recommend this impressive book very enthusiastically to both young and senior researchers interested in shape-restricted nonparametric estimation. Closing an important gap in the literature, it contains not only classical material on nonparametric estimation of monotone functions in a series of application fields but also an introduction to advanced themes that are the topic of active ongoing research - in particular, estimation of convex functions, interval censoring, higher dimensional models, and other complex models in order-restricted inference. Interesting and enjoyable, the book clearly motivates models and methods by illustrative data examples and intuitive heuristic explanations of the necessary asymptotic mathematical theory, accompanied by clear and detailed proofs of the theory.' Enno Mammen, Institute of Applied Mathematics, Heidelberg University

    'A comprehensive study of the state of the art in nonparametric shape-restricted inference by two experts in the field. A clear-cut cogent presentation style, along with a careful exposition of the mathematics as well as the algorithmic aspects of the optimization problems involved, makes this a very well-rounded text that should prove an asset to both mathematically trained scientists seeking a rigorous exposure to the field and statistical researchers interested in the 'current status' of affairs in shape-restricted inference.' Moulinath Banerjee, University of Michigan, Ann Arbor

    'The book provides an up-to-date comprehensive review of both classical and new methods for shape constrained estimators. It does so in a clear and well-explained manner, including many real-world examples to motivate the methodology and theory. As such it contains a nice mix of theory and applications, and so should be of interest to both students and researchers. … I thoroughly enjoyed reading this book: it gives a detailed treatment of most relevant features of shape constrained estimation, and does so in a manner that makes it immensely readable, whether you are a novice or an expert in the area.' Dennis Kristensen, MathSciNet Mathematical Reviews (www.ams.org/mr-database)

    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 2014
    • format: Hardback
    • isbn: 9780521864015
    • length: 428 pages
    • dimensions: 261 x 184 x 27 mm
    • weight: 0.93kg
    • contains: 90 b/w illus. 20 tables 190 exercises
    • availability: In stock
  • Table of Contents

    1. Introduction
    2. Basic estimation problems with monotonicity constraints
    3. Asymptotic theory for the basic monotone problems
    4. Other univariate problems involving monotonicity constraints
    5. Higher dimensional problems
    6. Lower bounds on estimation rates
    7. Algorithms and computation
    8. Shape and smoothness
    9. Testing and confidence intervals
    10. Asymptotic theory of smooth functionals
    11. Pointwise asymptotic distribution theory for univariate problems
    12. Pointwise asymptotic distribution theory for multivariate problems
    13. Asymptotic distribution of global deviations.

  • Authors

    Piet Groeneboom, Technische Universiteit Delft, The Netherlands
    Piet Groeneboom is Professor Emeritus of Statistics at Delft University of Technology, The Netherlands.

    Geurt Jongbloed, Technische Universiteit Delft, The Netherlands
    Geurt Jongbloed is Professor of Statistics at Delft University of Technology, The Netherlands.

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.
×