Constrained optimal discrimination designs for Fourier regression models

被引：11

作者：

Biedermann, Stefanie ^{[2
]}

Dette, Holger ^{[1
]}

Hoffmann, Philipp ^{[1
]}

机构：

[1] Ruhr Univ Bochum, Fak Math, D-44780 Bochum, Germany

[2] Univ Southampton, Sch Math, Southampton SO17 1BJ, Hants, England

来源：

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2009年 / 61卷 / 01期

关键词：

Constrained optimal designs; Trigonometric regression; D-1-optimal designs; Chebyshev polynomials; Canonical moments; POLYNOMIAL REGRESSION; EQUIVALENCE; SHAPE;

D O I：

10.1007/s10463-007-0133-5

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this article, the problem of constructing efficient discrimination designs in a Fourier regression model is considered. We propose designs which maximize the power of the F-test, which discriminates between the two highest order models, subject to the constraints that the tests that discriminate between lower order models have at least some given relative power. A complete solution is presented in terms of the canonical moments of the optimal designs, and for the special case of equal constraints even more specific formulae are available.

引用

页码：143 / 157

页数：15

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