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Variance components

WILEY-INTERSCIENCE PAPERBACK SERIES. The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of the...

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Bibliographic Details
Main Authors: Searle, S. R. Shayle R., 1928
Group Author: Casella, George; McCulloch, Charles E
Published:
Literature type: Electronic eBook
Language: English
Series: Wiley series in probability and mathematical statistics. Applied probability and statistics
Subjects:
Analysis of variance
Analyse de variance
MATHEMATICS > Probability & Statistics > General
Variantieanalyse
Multivariate analysis
Electronic books
Online Access: http://onlinelibrary.wiley.com/book/10.1002/9780470316856
Summary: WILEY-INTERSCIENCE PAPERBACK SERIES. The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .Variance Components is an excellent book. It is organized and well written, and provides many references to a variety of topics. I recommend it to anyone with interest in linear models."
Item Description: "A Wiley-Interscience publication."
Carrier Form: 1 online resource (xxiii, 501 pages).
Bibliography: Includes bibliographical references (pages 475-489) and index.
ISBN: 9780470316856
0470316853
9780470317693 (electronic bk.)
0470317698 (electronic bk.)
Index Number: QA279
CLC: O212.1
Contents: Variance Components; CONTENTS; 1. Introduction; 2. History and Comment; 3. The I-Way Classification; 4. Balanced Data; 5. Analysis of Variance Estimation for Unbalanced Data; 6. Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML); 7. Prediction of Random Variables; 8. Computing ML and REML estimates; 9. Hierarchical Models and Bayesian Estimation; 10. Binary and Discrete Data; 11. Other Procedures; 12. The Dispersion-Mean Model; Appendix F. Estimation Formulae for Unbalanced Data; PART II. THE 2-WAY CROSSED CLASSIFICATION; Appendix M. Some Results in Matrix Algebra.

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