E-OPTIMAL DESIGNS FOR POLYNOMIAL REGRESSION

• 成果类型: Article
• 署名作者: PUKELSHEIM, F; STUDDEN, WJ
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Purdue University System; Purdue University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176349033
• 发表日期: 1993
• 页码: 402-415
• 关键词: LINEAR-REGRESSION

摘要

E-optimal designs for the full mean parameter vector, and for many subsets in univariate polynomial regression models are determined. The derivation is based on the interplay between E-optimality and scalar optimality. The scalar parameter systems are obtained as transformations of the coefficient vector c of the Chebyshev polynomial.