Likelihood Methods in Statistics by Thomas A. SeveriniLikelihood Methods in Statistics by Thomas A. Severini

Likelihood Methods in Statistics

byThomas A. Severini

Hardcover | September 15, 2000

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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 probabilityapproximations 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 methodshave 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.
Thomas A. Severini is at Northwestern University Evanston, Illinois.
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Title:Likelihood Methods in StatisticsFormat:HardcoverPublished:September 15, 2000Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198506503

ISBN - 13:9780198506508

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Editorial Reviews

"This book presents an excellent overview of modern likelihood methods. The presentation is clear and readable enough to be of considerable use to intermediate level graduate students, but is complete and up-to-date enough to act as an excellent first reference for beginning researchers in the field. . . . Moreover, there are excellent discussions of important references as well as numerous exercises. . . . The field of likelihood asymptotics has been undergoing an increasingly rapid development over the last two decades, and this book provides an excellent and detailed account of where the field is, where it came from and perhaps even a bit about where it is going." -- Mathematical Reviews