Likelihood methods play a central role in statistical theory and methodology. Recently, a new approach to likelihood inference has been developed that often leads to substantial improvements over classical methods. This book gives a detailed introduction to this modern theory of likelihood methods. Series: Oxford Statistical Science Series. Num Pages: 392 pages, illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 240 x 162 x 29. Weight in Grams: 720. . 2000. Hardback. . . . . Books ship from the US and Ireland.

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Bibliographic Details

Title: Likelihood Methods in Statistics
Publisher: Oxford University Press
Publication Date: 2001
Language: English
ISBN 10: 0198506503
ISBN 13: 9780198506508
Binding: Hardcover
Condition: New

About this title

Synopsis

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 provide an up-to-date account of recent results in the field, which has been undergoing rapid development.

About the Author

Thomas A. Severini is at Northwestern University Evanston, Illinois.

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