期刊
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
卷 136, 期 9, 页码 3231-3247出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jspi.2005.01.007
关键词
design of experiment; Latin hypercube; genetic algorithm
A crucial component in the statistical simulation of a computationally expensive model is a good design of experiments. In this paper we compare the efficiency of the columnwise-pairwise (CP) and genetic algorithms for the optimization of Latin hypercubes (LH) for the purpose of sampling in statistical investigations. The performed experiments indicate, among other results, that CP methods are most efficient for small and medium size LH, while an adopted genetic algorithm performs better for large LH. Two optimality criteria suggested in the literature are evaluated with respect to statistical properties and efficiency. The obtained results lead us to favor a criterion based on the physical analogy of minimization of forces between charged particles suggested in Audze and Eglais (1977. Problems Dyn. Strength 35, 104-107) over a 'maximin distance' criterion from Johnson et al. (1990. J. Statist. Plann. Inference 26, 131-148). (c) 2005 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据