AJP - Regulatory, Integrative and Comparative Physiology, Vol 248, Issue 3 378-R386, Copyright © 1985 by American Physiological Society
Multiple-objective criteria for optimal experimental design: application to ferrokinetics
M. H. Nathanson and G. M. Saidel
Optimal experimental design is used to predict the experimental conditions
that will allow the "best" estimates of model parameters. A variety of
criteria must be considered before an optimal design is chosen. Maximizing
the determinant of the information matrix (D optimality), which tends to
produce the most precise simultaneous estimates of all parameters, is
commonly considered as the primary criterion. To complement this criterion,
we present another whose effect is to reduce the interaction among the
parameter estimates so that changes in any one parameter can be more
distinct. This new criterion consists of maximizing the determinant of an
appropriately scaled information matrix (M optimality). These criteria are
applied jointly in a multiple-objective function. To illustrate the use of
these concepts, we develop an optimal experimental design of blood sampling
schedules using a detailed ferrokinetic model.
