Linear Regression Analysis: Theory and Computing
Linear Regression Analysis: Theory and Computing
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DOI：
10.1142/6986
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发表时间：
2009-06
期刊：
影响因子：
--
通讯作者：
Xin Yan;Xiaogang Su
中科院分区：
文献类型：
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作者：
Xin Yan;Xiaogang Su
本书详细介绍了线性回归分析和诊断的基本理论，以及相关的统计计算技术，使读者能够使用书中描述的方法和技术实际建模数据。它涵盖了线性回归分析的基本理论，对这一领域的未来研究非常有用。文中还包括使用统计应用系统(SAS)进行回归分析的例子。这本书适合统计学/生物统计学专业的研究生，或者在他们的学科领域大量使用线性回归分析的研究生。多元线性回归模型选择模型诊断最小二乘广义线性模型贝叶斯回归的扩展
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. Introduction 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