This Title All WIREs
How to cite this WIREs title:
WIREs Comp Stat

Diagnostic procedures

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Diagnostic procedures are used to check the quality of a fit of a model, to verify the validity of the assumptions behind the model, and to find outlying and/or highly influential observations. Our discussion focuses on the linear model (the most widely used model). Much of our discussion, however, pertains to other models, as we show when we extend our discussion to mixed models at the end of the paper. The traditional fit, least squares (LS), can be severely impaired by just one outlier. So along with LS we present two robust fits and diagnostic procedures which explore the differences among the three fits. These comparisons generally find the outlying and influential cases. Armed with this methodology, we then proceed to discuss diagnostics that explore the quality of fit and verify the validity of the assumptions, including independent and identically distributed errors and normality. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Statistical Models > Linear Models Statistical and Graphical Methods of Data Analysis > Robust Methods Statistical Models > Fitting Models Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization

Plots for the bonds data.

[ Normal View | Magnified View ]

Studentized residual plots of model 19..

[ Normal View | Magnified View ]

Related Articles

Exploratory data analysis

Browse by Topic

Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization
Statistical Models > Fitting Models
Statistical and Graphical Methods of Data Analysis > Robust Methods
Statistical Models > Linear Models

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts