Empirical Likelihood

Art B. Owen

May 18, 2001 by Chapman and Hall/CRC
Reference - 304 Pages - 40 B/W Illustrations
ISBN 9781584880714 - CAT# C0326
Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

was $125.95

USD$100.76

SAVE ~$25.19

Add to Wish List
SAVE 25%
When you buy 2 or more print books!
See final price in shopping cart.
FREE Standard Shipping!

Features

  • Illustrates the method's broad applicability through a wide range of data sets
  • Shows how to make nonparametric inferences through a likelihood interface
  • Details the method's advantages over the bootstrap for two- and higher- dimensional models
  • Demonstrates how this method automatically chooses from the data the shape of a confidence region
  • Describes how it is easy to incorporate side information, such as a known mean, for one or more of the random quantities observed
  • Discusses other nonparametric likelihoods, including Euclidean and entropy likelihoods
  • Furnishes Web support-algorithms, software, and links-at www.stanford.edu/~owen/empirical
  • Summary

    Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It also facilitates incorporating side information, and it simplifies accounting for censored, truncated, or biased sampling.

    One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies empirical likelihood to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Abundant figures offer visual reinforcement of the concepts and techniques. Examples from a variety of disciplines and detailed descriptions of algorithms-also posted on a companion Web site at-illustrate the methods in practice. Exercises help readers to understand and apply the methods.

    The method of empirical likelihood is now attracting serious attention from researchers in econometrics and biostatistics, as well as from statisticians. This book is your opportunity to explore its foundations, its advantages, and its application to a myriad of practical problems.