Methods and applications of linear models
regression and the analysis of variance
Hocking, Ronald R.
creator
text
bibliography
nju
New Jersey
John Wiley
c2013
2013
3rd ed
monographic
eng
xxiii, 681 p. : illustrations ; 25 cm.
"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"--
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.
Ronald R. Hocking.
Includes bibliographical references (pages 669-676) and index.
Regression analysis
Analysis of variance
Linear models (Statistics)
MATHEMATICS / Probability & Statistics / General
000SA.062 H685
Wiley series in probability and statistics
9781118329504 (hardback)
ISI Library
130409
20150526114315.0
135769