Robust designs for Haar wavelet approximation models

Xiaojian Xu and Lin Zhao

Applied Stochastic Models in Business and Industry, 2011, vol. 27, issue 5, 531-550

Abstract: 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.

Date: 2011
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https://doi.org/10.1002/asmb.861

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:27:y:2011:i:5:p:531-550

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