Likelihood Methods in Statistics

Research output: Book/ReportBook

Abstract

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.
Original languageEnglish
PublisherOxford University Press
ISBN (Print)0198506503
StatePublished - 2000

Fingerprint

Dive into the research topics of 'Likelihood Methods in Statistics'. Together they form a unique fingerprint.

Cite this