Minimaxity for Randomized Designs: Some General Results

Abstract

In many design settings where model violations are present, a "stochastic" minimaxity for many standard randomization procedures is demonstrated. This result requires no special analytic properties of the loss function and estimators. Next, under the squared loss and with the restriction to the use of linear estimators, a recipe for finding a randomized strategy is given. As a special case, randomizing an $A$-optimal design in the standard manner and using the least squares estimates yields a minimax strategy in most cases. These results generalize some aspects of Wu (1981).