MINIMAX AND MAXIMIN DISTANCE DESIGNS

被引：1019

作者：

JOHNSON, ME

MOORE, LM

YLVISAKER, D

机构：

[1] GEORGIA INST TECHNOL,ATLANTA,GA 30332

[2] UNIV CALIF LOS ALAMOS SCI LAB,LOS ALAMOS,NM 87545

[3] UNIV CALIF LOS ANGELES,LOS ANGELES,CA 90024

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 1990年 / 26卷 / 02期

基金：

美国国家科学基金会;

关键词：

asymptotic optimality; Bayesian design; computer experiments;

D O I：

10.1016/0378-3758(90)90122-B

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：

Beginning with an arbitrary set and a distance defined on it, we develop the notions of minimax and maximin distance sets (designs). These are intended for use in the selection-of-sites problem when the underlying surface is modeled by a prior distribution and observations are made without error. It is shown that such designs have quite general asymptotically optimum (and dual) characteristics under what are termed the G- and D-criteria. There are many examples given, dealing espeacially with the unit square and with k factors at two levels. © 1990.

引用

页码：131 / 148

页数：18

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