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An application of the D-optimal criterion to define the experimental design for a particular class of semi-parametric
1Department of Laboratory Medicine, School of Medicine, University of California, San Francisco 94143.
Abstract:
An updated version of the computer program EXCAD [1] allows the user to optimize experimental design to estimate parameters of particular semi-parametric models. The semi-parametric models take the general form of a function of time (t): Y(t) = NL (c(t,alpha),beta). The function NL(C(t,alpha),beta), is, in general, a non-linear transformation of a function, C(t,alpha), that in turn is the convolution of two others. One of these two functions is expressed in a non-parametric form, and is not of direct interest to the experimenter. The other is of direct interest: it is a parametric function depending on a set of parameters alpha. This semi-parametric model applies to numerous kinds of biological experiments, such as pharmacokinetic/pharmacodynamic, physiological, circulatory flow experiments. This paper presents a new method for determining an optimal experimental design to estimate the parameters alpha and beta. The new approach adopts the D-optimal criterion, and is illustrated using real thiopental data.