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...