A SAS/IML Companion for Linear Models

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...

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Bibliographic Details
Main Author: Perrett, Jamis J. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer New York, 2010.
Series:Statistics and Computing,
Subjects:
Online Access:Full Text via HEAL-Link
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 Computation Methods.