Methods and Applications of Linear Models: Regression and the Analysis of Variance
Rights Contact Login For More Details
- Wiley
More About This Title Methods and Applications of Linear Models: Regression and the Analysis of Variance
English
Ronald R. Hocking is Professor Emeritus in the Department of Statistics at Texas A&M University. He received his PhD in mathematics and statistics and is a Fellow of the American Statistical Association.
English
Partial table of contents:
INTRODUCTION AND BASIC THEORY.
Introduction to Linear Models.
Estimation and Inference In Simple Linear Models.
REGRESSION MODELS.
Transforming the Data and Miscellaneous Topics.
Regression on Functions of Several Variables.
Influential Observations in Multiple Linear Regression.
Related Topics.
ANALYSIS OF VARIANCE MODELS.
Fixed Effect Models: I. Single-Factor Classification of Means.
Fixed Effects Models: III.
Nested Factors and General Structure.
Mixed Effects Models: II.The AVE Method.
Mixed Effects Models: III.
Unbalanced Data.
Appendices.
References.
Index.
