In 1992, Doulas Wiens suggested a problem that considers the optimal design minimizing the variance of the estimator of the parameters of regression function when the fitted model is correct, subject to a bound on the bias term which occurs when the true model is different from the assumed one. The corresponding optimal designs can be called bounded bias optimal designs. Some general results for D-optimality was obtained and published (see Liu and Wiens, 1997). In this paper, we study mainly A-optimal designs. For some special cases of bounded functions, explicitly design measures are given.
