Verotta D
Department of Laboratory Medicine, School of Medicine, University of California, San Francisco 94143.
Comput Methods Programs Biomed. 1990 Nov;33(3):181-7. doi: 10.1016/0169-2607(90)90041-7.
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.
计算机程序EXCAD的更新版本[1]允许用户优化实验设计，以估计特定半参数模型的参数。半参数模型采用时间（t）函数的一般形式：Y(t) = NL (c(t,alpha),beta)。函数NL(C(t,alpha),beta)通常是函数C(t,alpha)的非线性变换，而C(t,alpha)又是另外两个函数的卷积。这两个函数中的一个以非参数形式表示，实验者对此并不直接感兴趣。另一个则是直接感兴趣的：它是一个依赖于一组参数alpha的参数函数。这种半参数模型适用于多种生物实验，如药代动力学/药效学、生理学、循环流量实验。本文提出了一种确定最优实验设计以估计参数alpha和beta的新方法。新方法采用D最优准则，并使用真实的硫喷妥数据进行了说明。
