Robust designs for Haar wavelet approximation models
Article first published online: 5 DEC 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Applied Stochastic Models in Business and Industry
Volume 27, Issue 5, pages 531–550, September/October 2011
How to Cite
Xu, X. and Zhao, L. (2011), Robust designs for Haar wavelet approximation models. Appl. Stochastic Models Bus. Ind., 27: 531–550. doi: 10.1002/asmb.861
- Issue published online: 18 OCT 2011
- Article first published online: 5 DEC 2010
- Manuscript Accepted: 13 JUL 2010
- Manuscript Revised: 6 MAR 2010
- Manuscript Received: 20 JUL 2009
- design discretization
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: G1 and G2. Our main findings are: (1) A recursive formula for constructing D-optimal designs under G1; (2) Equivalency of Q-optimal and A-optimal designs under both G1 and G2; (3) D-optimal robust designs under G2; and (4) Analytic forms for A- and Q-optimal robust design densities under G2. Several examples are given for the comparison, and the results demonstrate that our designs are efficient. Copyright © 2010 John Wiley & Sons, Ltd.