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Likelihood Methods in Statistics (Oxford Statistical Science Series)

Thomas A. Severini · 2000

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About the book

"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 to often 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."--Jacket.

Book details

Year
2000
Language
English
Series
Oxford Statistical Science
Publisher
Oxford University Press, USA
Editions
1
Pages
392
ISBN
9780198506508

Data source: Wikidata

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