Robust Designs for Approximate Regression Models with Correlated Errors

We summarize recent ...ndings on the construction of designs, to be used in experiments for which regression is the anticipated method of analysis. The designs are to be robust against departures from the assumed linear response and/or departures from the assumption of uncorrelated errors. Included is a discussion of an “in...nitesimal” approach to design. In this approach one aims to minimize the determinant of the mean squared error matrix of the regression estimates, subject to the satisfaction of a robustness constraint. The constraint is quanti...ed in terms of boundedness of the Gateaux derivative of this determinant, in the direction of a contaminating response function or autocorrelation structure.