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Heteroscedastic G-Optimal Designs

Weng Kee Wong, R. Dennis Cook

Journal of the Royal Statistical Society: Series B (Statistical Methodology) · 1993 · Volume 55 · Issue 4

DOI: 10.1111/j.2517-6161.1993.tb01946.x

Abstract

This paper addresses the issue of constructing large sample G-optimal designs when the variability of the response varies across a compact design space. A useful characterization theorem is presented along with a computer algorithm for generating (heteroscedastic) G-optimal designs. to facilitate comparisons between D- and G-optimal designs, Atwood's inequality for comparing D- and G-efficiencies in homoscedastic models is generalized to heteroscedastic models. Some robustness properties of these designs are presented.

Keywords

design efficiency, D optimal, G optimal, heteroscedasticity, information matrix, large sample design

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