Linear statistical models: Linear regression and analysis of variance

Author: Wang Songgui
Publisher:
Publish Date: 2003-08-01
Features: This book is a research outcome of the "Reform Plan for Teaching Content and Curriculum System in Higher Education Towards the 21st Century" by the Ministry of Education. It is a 21st-century curriculum textbook that primarily teaches linear regression models and analysis of variance models. The content includes normal distribution, least squares estimation, ridge estimation, principal component estimation, regression diagnostics, hypothesis testing and prediction, selection of regression equations, and analysis of variance. It also provides a general introduction to several linear regression models with more complex error structures. The first six chapters of the book are accompanied by an appropriate number of exercises, and the appendix offers detailed proofs of important facts in matrix theory used in the book. This book can serve as a textbook for undergraduate or graduate students in disciplines related to science, engineering, agriculture, medicine, economics, management, and other fields in higher education. The book primarily teaches linear regression models and analysis of variance models, including normal analysis, least squares estimation, ridge estimation, principal multiple estimation, regression diagnostics, etc.