  Expected Fisher information can be found a priori and as a result its inverse
is the primary variance approximation used in the design of experiments. This
is in contrast to the common claim that the inverse of observed Fisher
information is a better approximation to the variance of the maximum likelihood
estimator. Observed Fisher information cannot be known a priori; however, if an
experiment is conducted sequentially (in a series of runs) the observed Fisher
information from previous runs is available. In the current work two adaptive
designs are proposed that use the observed Fisher information from previous
runs in the design of the current run.
