MINIMAX SECOND-ORDER DESIGNS OVER CUBOIDAL REGIONS FOR THE DIFFERENCE BETWEEN TWO ESTIMATED RESPONSES

被引：7

作者：

Huda, S. ^{[1
]}

Mukerjee, Rahul ^{[2
]}

机构：

[1] Kuwait Univ, Fac Sci, Dept Stat, Safat 13060, Kuwait

[2] Indian Inst Management Calcutta, Kolkata 700104, India

来源：

INDIAN JOURNAL OF PURE & APPLIED MATHEMATICS | 2010年 / 41卷 / 01期

关键词：

Central composite design; convexity; surrogate objective function; VARIANCE FUNCTION;

D O I：

10.1007/s13226-010-0006-0

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Minimization of the variance of the difference between estimated responses at two points, maximized over all pairs of points in the factor space, is taken as the design criterion. Optimal designs under this criterion are derived, via a combination of algebraic and numerical techniques, for the full second-order regression model over cuboidal regions. Use of a convexity argument and a surrogate objective function significantly reduces the computational burden.

引用

页码：303 / 312

页数：10

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