Robust designs for Haar wavelet approximation models

In this paper, we discuss the construction of robust designs for heteroscedastic wavelet regression models when the assumed models are possibly contaminated over two different neighbourhoods: G ₁ and G ₂ . Our main findings are: (1) A recursive formula for constructing D‐optimal designs under G ₁ ; (2) Equivalency of Q‐optimal and A‐optimal designs under both G ₁ and G ₂ ; (3) D‐optimal robust designs under G ₂ ; and (4) Analytic forms for A‐ and Q‐optimal robust design densities under G ₂ . Several examples are given for the comparison, and the results demonstrate that our designs are efficient. Copyright © 2010 John Wiley & Sons, Ltd.