
Likelihood Methods in Statistics
Thomas A. Severini(Author)
Oxford University Press
Published on 9. November 2000
Book
Hardback
392 pages
978-0-19-850650-8 (ISBN)
Description
This book provides an introduction to the modern theory of likelihood-based statistical inference. This theory is characterized by several important features. One is the recognition that it is desirable to condition on relevant ancillary statistics. Another is that probability approximations are based on saddlepoint and closely related approximations that generally have very high accuracy. A third aspect is that, for models with nuisance parameters, inference is often based on marginal or conditional likelihoods, or approximations to these likelihoods. These methods have been shown often to yield substantial improvements over classical methods. The book also provides an up-to-date account of recent results in the field, which has been undergoing rapid development.
Reviews / Votes
This book is an excellent account of likelihood-based statistical inference; I believe that it will be a very useful addition to any scholarly library. * Biometrics *More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 26 mm
Weight
757 gr
ISBN-13
978-0-19-850650-8 (9780198506508)
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Schweitzer Classification
Person
Author
Department of StatisticsDepartment of Statistics, Northwestern University Evanston, Illinois