Abstract
The use of Stein estimation in multiple linear regression is considered. Tables and graphs are presented that compare the prediction mean squared errors of positive-part James-Stein, preliminary-test, reduced, and full-model least squares estimates. The appropriateness of using Stein contraction on possibly extraneous variables is emphasized, and a procedure is presented for evaluating the likely savings in using Stein estimation on the problem at hand. An example is given.
| Original language | English |
|---|---|
| Pages (from-to) | 113-121 |
| Number of pages | 9 |
| Journal | Technometrics |
| Volume | 28 |
| Issue number | 2 |
| DOIs | |
| State | Published - May 1986 |
Keywords
- Prediction mean squared error
- Preliminary test estimators
- Stein estimators