Introduction to Linear Models

Author: Wang Songgui
Publisher:
Publish Date: 2004-05-01
Features: This book systematically elaborates on the basic theories, methods, and applications of linear models, including recent developments in both theory and application. The book is divided into nine chapters. Chapter 1 introduces various linear models through examples. Chapter 2 discusses supplementary knowledge in matrix theory. Chapter 3 covers multivariate normal distributions and related distributions. Starting from Chapter 4, the book systematically discusses the fundamental theories and methods of statistical inference in linear models, including: least squares estimation, hypothesis testing, confidence regions, prediction, linear regression models, analysis of variance models, analysis of covariance models, and linear mixed-effects models. This book can serve as a textbook for senior undergraduate, master's, or doctoral students in mathematics departments, mathematical statistics or statistics departments, biostatistics departments, and econometrics departments, as well as for reference books for teachers or scientific and technical workers in fields such as mathematics, biology, medicine, engineering, economics, and finance. University Mathematics Science Series.