In several key functional areas of contemporary engineering and management science, neural networks have steadily been gaining recognition as robust and reliable tools for classification problems. This paper describes a new application of the learning vector quantization neural network: the...

This paper investigates the robustness of designed experiments for estimating linear functions of a subset of parameters in a general linear model against the loss of any t( U 1) observations. Necessary and sufficient conditions for robustness of a design under a homoscedastic model are derived....

The universal optimality of some block designs with unequal block sizes is studied, under the usual homoscedastic model and under a certain heteroscedastic model.