  The experimental design for a generalized linear model (GLM) is important but
challenging since the design criterion often depends on model specification
including the link function, the linear predictor, and the unknown regression
coefficients. Prior to constructing locally or globally optimal designs, a
pilot experiment is usually conducted to provide some insights on the model
specifications. In pilot experiments, little information on the model
specification of GLM is available. Surprisingly, there is very limited research
on the design of pilot experiments for GLMs. In this work, we obtain some
theoretical understanding of the design efficiency in pilot experiments for
GLMs. Guided by the theory, we propose to adopt a low-discrepancy design with
respect to some target distribution for pilot experiments. The performance of
the proposed design is assessed through several numerical examples.
