Yan X., Su X.G. Linear Regression Analysis: Theory and Computing

Yan X., Su X.G. Linear Regression Analysis: Theory and Computing
World Scientific Publishing Co. Pte. Ltd. | 2009 | ISBN-10: 9812834109 | 349 pages
by Xin Yan (University of Missouri–Kansas City, USA) & Xiao Gang Su (University of Central Florida, USA)
This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields.
These illustrative programs are often arranged in the end of each chapter with brief explanations. In addition to the SAS, we also briefly introduce the software R which is a freeware. R has many user-written functions for implementation of various statistical methods including regression. These functions are similar to the builtin functions in the commercial software package S-PLUS. We provide some programs in R to produce desired regression diagnosis graphs. Readers are encouraged to learn how to use the software R to perform regression analysis, diagnosis, and producing graphs.Simple Linear Regression
Multiple Linear Regression
Detection of Outliers and Influential Observations in Multiple Linear Regression
Model Selection
Model Diagnostics
Extensions of Least Squares
Generalized Linear Models
Bayesian Linear Regression