  Optimal designs for generalized linear models require a prior knowledge of
the regression parameters. At certain values of the parameters we propose
particular assumptions which allow to derive a locally optimal design for a
model without intercept from a locally optimal design for the corresponding
model with intercept and vice versa. Applications to Poisson and logistic
models and Extensions to nonlinear models are provided.
