Designing experiments under random contamination with application to polynomial spline regression
In science and engineering, there is often uncertainty in the linear model assumed for a response when an experiment is being designed. The errors in predictions made from a fitted model may then be more dependent on the systematic errors (bias) that arise from model misspecification than from error...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
2005.
|
| Subjects: | |
| Online Access: | Get fulltext |