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Methods and applications of linear models : regression and the analysis of variance / Ronald R. Hocking.

By: Material type: TextTextSeries: Wiley series in probability and statisticsPublication details: New Jersey : John Wiley, c2013.Edition: 3rd edDescription: xxiii, 681 p. : illustrations ; 25 cmISBN:
  • 9781118329504 (hardback)
Subject(s): DDC classification:
  • 000SA.062 23 H685
Contents:
1. Introduction to linear models-- 2. Regression on functions of one variable-- 3. Transforming the data-- 4. Regression on functions of several variables-- 5. Collinearity in multiple linear regression-- 6. Influential observations in multiple linear regression-- 7. Polynomial models and qualitative predictors-- 8. Additional topics-- 9. Classification models I: Introduction-- 10. The mathematical theory of linear models-- 11. Classification models II: Multiple crossed and nested factors-- 12. Mixed models I: The AOV method with blanced data-- 13. Mixed models II: The AVE method with balanced data-- 14. Mixed models III: Unbalanced data-- 15. Simultaneous inference: Tests and confidence intervals-- Appendices-- References-- Index.
Summary: "The new edition of this "essential desktop reference book. [that] should definitely be on your bookshelf" (Technometrics) features a newly reorganized approach to linear regression that promotes the understanding of theory and models concurrently, featuring newly-developed topics in the field and the use of software applications. It includes numerous exercises; graphics and computations developed using JMP software; a new chapter on recent developments with the distribution of linear and quadratic forms; and new topical coverage of least squares, the cell means model, and more"--Summary: "The objective of this book is to present a discussion and a formal definition of a general class of linear models"--
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.062 H685 (Browse shelf(Opens below)) Available 135769
Total holds: 0

Includes bibliographical references (pages 669-676) and index.

1. Introduction to linear models--
2. Regression on functions of one variable--
3. Transforming the data--
4. Regression on functions of several variables--
5. Collinearity in multiple linear regression--
6. Influential observations in multiple linear regression--
7. Polynomial models and qualitative predictors--
8. Additional topics--
9. Classification models I: Introduction--
10. The mathematical theory of linear models--
11. Classification models II: Multiple crossed and nested factors--
12. Mixed models I: The AOV method with blanced data--
13. Mixed models II: The AVE method with balanced data--
14. Mixed models III: Unbalanced data--
15. Simultaneous inference: Tests and confidence intervals--
Appendices--
References--
Index.

"The new edition of this "essential desktop reference book. [that] should definitely be on your bookshelf" (Technometrics) features a newly reorganized approach to linear regression that promotes the understanding of theory and models concurrently, featuring newly-developed topics in the field and the use of software applications. It includes numerous exercises; graphics and computations developed using JMP software; a new chapter on recent developments with the distribution of linear and quadratic forms; and new topical coverage of least squares, the cell means model, and more"--

"The objective of this book is to present a discussion and a formal definition of a general class of linear models"--

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