On Optimal Designs for Nonlinear Models: A General and Efficient Algorithm
On Optimal Designs for Nonlinear Models: A General and Efficient Algorithm
复制标题
非线性模型的优化设计：一种通用且高效的算法
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Elina Tang
中科院分区：
文献类型：
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作者：
Min Yang;Stefanie Biedermann;Elina Tang
一般来说，寻找非线性模型的最优设计是具有挑战性的。虽然最近的一些结果，使我们能够专注于一个简单的子类设计的大多数问题，得出一个特定的最优设计仍然主要取决于数值方法。需要一种通用且有效的算法，其比当前最先进的方法更广泛地适用。我们提出了一种新的算法，可以用来找到最优设计的最优性标准的广泛的类，当模型参数或功能的利益，并为本地最优和多级设计策略。我们证明了收敛到最优设计，并在各种例子中表明，新算法优于目前最先进的算法。
Finding optimal designs for nonlinear models is challenging in general. Although some recent results allow us to focus on a simple subclass of designs for most problems, deriving a specific optimal design still mainly depends on numerical approaches. There is need for a general and efficient algorithm that is more broadly applicable than the current state-of-the-art methods. We present a new algorithm that can be used to find optimal designs with respect to a broad class of optimality criteria, when the model parameters or functions thereof are of interest, and for both locally optimal and multistage design strategies. We prove convergence to the optimal design, and show in various examples that the new algorithm outperforms the current state-of-the-art algorithms.