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Global sensitivity indices play important
roles in global sensitivity analysis based on ANOVA high-dimensional
representation, Wang et al. (2012) showed that orthogonal arrays
are A-optimality designs for the estimation of parameter ,
the definition of which can be seen in Section 2. This paper
presented several other optimal properties of orthogonal arrays
under ANOVA high-dimensional representation, including E-optimality
for the estimation of  and universal optimality for the
estimation of , where  is the independent
parameters of . Simulation study showed that randomized
orthogonal arrays have less biased and more precise in estimating
the confidence intervals comparing with other methods.