Robustness in spatial studies II: minimax design

We consider robust methods for the construction of sampling designs in spatial studies. The designs are robust against misspecified regression responses, and are tailored for possible use with predictors which are minimax robust against misspecified variance/covariance structures. The loss function is based on the mean squared error of the predicted values. This is maximized, analytically, over a neighbourhood quantifying the departures from the fitted linear regression response. This maximum is then minimized numerically—by simulated annealing, or sequentially—in order to obtain the optimal designs. Copyright # 2004 John Wiley & Sons, Ltd. key words: anisotropic; computer experiments; generalized M-estimation; isotropic; kriging; minimax; M-estimate; sequential; simulated annealing 1