Linear Regression Analysis: Theory and Computing

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World Scientific, 2009 - Mathematics - 348 pages
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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.
 

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Contents

1 Introduction
1
2 Simple Linear Regression
9
3 Multiple Linear Regression
41
4 Detection of Outliers and Inuential Observations in Multiple Linear Regression
129
5 Model Selection
157
6 Model Diagnostics
195
8 Generalized Linear Models
269
9 Bayesian Linear Regression
297
Bibliography
317
Index
325
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