ABSTRACT

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least square

chapter 1|22 pages

Review of Fundamentals of Statistics

chapter 3|82 pages

Misspecifi ed Disturbance Terms

chapter 4|14 pages

Nonparametric Regression

chapter 5|62 pages

Logistic Regression

chapter 6|20 pages

Bayesian Regression

chapter 7|26 pages

Robust Regression

chapter 8|36 pages

Fuzzy Regression

chapter 9|38 pages

Random Coeffi cients Regression

chapter 10|14 pages

L1 and q-Quantile Regression

chapter 11|16 pages

Regression in a Spatial Domain

chapter 12|94 pages

Multiple Regression

chapter 13|36 pages

Normal Correlation Models

chapter 14|18 pages

Ridge Regression

chapter 15|20 pages

Indicator Variables

chapter 16|56 pages

Polynomial Model Estimation

chapter 17|28 pages

Semiparametric Regression

chapter 18|42 pages

Nonlinear Regression