A SAS/IML Companion for Linear Models

• Main Author: Perrett, Jamis J. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York, 2010.
• Series: Statistics and Computing,
• Subjects: Statistics.; Mathematical statistics.; Statistical Theory and Methods.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-5557-9

Linear models courses are often presented as either theoretical or applied. Consequently, students may find themselves either proving theorems or using high-level procedures like PROC GLM to analyze data. There exists a gap between the derivation of formulas and analyses that hide these formulas beh...

Table of Contents:

• SAS/IML: A brief introduction
• IML language structure
• IML programming features
• Matrix manipulations in SAS/IML
• Mathematical and statistical basics
• Linear algebra
• The Multivariate Normal Distribution
• The General Linear Model
• Linear mixed models
• Statistical Computational Methods
• In summary.