Optimal experimental designs when some independent variables are not subject to control

• 成果类型: Article
• 署名作者: López-Fidalgo, J; Garcet-Rodríguez, SA
• 署名单位: University of Salamanca
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214504000001736
• 发表日期: 2004
• 页码: 1190-1199
• 关键词: regression-model

摘要

This article considers the problem of constructing optimal designs for regression models when the design space is a product space and some of the variables are not under the control of the practitioner. A variable that is not tinder control can have known values before the experiment is performed or else unknown values before the experiment is realized. The first case is briefly discussed in the literature. The aim of this work is to provide equivalence theorems for the second case and the mixture of both cases. Iterative algorithms for generating approximate optimal designs are given, and a real case of lung cancer is discussed.