Optimal Designs for Quantile Regression Models

• 成果类型: Article
• 署名作者: Dette, Holger; Trampisch, Matthias
• 署名单位: Ruhr University Bochum
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2012.695665
• 发表日期: 2012
• 页码: 1140-1151
• 关键词: paclitaxel; robust; emax; DRUG

摘要

Despite their importance, optimal designs for quantile regression models have not been developed so far. In this article, we investigate the D-optimal design problem for nonlinear quantile regression analysis. We provide a necessary condition to check the optimality of a given design and use it to determine bounds for the number of support points of locally D-optimal designs. The results are illustrated, determining locally, Bayesian and standardized maximin D-optimal designs for quantile regression analysis in the Michaelis-Menten and EMAX model, which are widely used in such important fields as toxicology, pharmacokinetics, and dose-response modeling.