Variance Components by Shayle R Searle

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Summary

Examines the estimation of variance components and the prediction of realized but unobservable values of random variables in both the analysis of variance models and in binary and discrete data. Major methods of estimating components are discussed, including ANOVA, ML, REML and Bayes.

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Variance Components by Shayle R Searle

This text presents a broad coverage of variance components. It deals with the estimation of variance components and the prediction of realized but unobservable values of random variables in analysis of variance models and in binary and discrete data. The authors begin with an introduction to the subject, which details more complicated types of data appearing in subsequent chapters. All the major methods of estimating components are discussed at length, including ANOVA, ML, REML, and Bayes. Topics covered include history, analysis of variance estimation, maximum likelihood (ML) estimation, prediction in mixed models, Bayes estimation and hierarchical models, categorical data, covariance components and minimum norm estimation, dispersion-mean model, kurtosis and fourth moments.
SKU Unavailable
ISBN 13 9780471621621
ISBN 10 0471621625
Title Variance Components
Author Shayle R Searle
Series Wiley Series In Probability And Statistics Ser
Condition Unavailable
Binding Type Hardback
Publisher John Wiley and Sons Ltd
Year published 1992-03-27
Number of pages 528
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.