Title

Minimax Distance Designs In 2-Level Factorial-Experiments

Authors

Authors

P. W. M. John; M. E. Johnson; L. M. Moore;D. Ylvisaker

Comments

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Abbreviated Journal Title

J. Stat. Plan. Infer.

Keywords

BAYESIAN DESIGN; COMPUTER EXPERIMENTS; DESIGN OPTIMALITY CRITERIA; 2-LEVEL FRACTIONAL FACTORIAL DESIGN; Statistics & Probability

Abstract

A minimax distance criterion was set forth in Johnson et al. (1990) for the purpose of selection among experimental designs. Unlike the usual design criteria such as D-, E- or G-optimality, minimax distance presumes no underlying model and, in turn, is not concerned with the rank of an associated design matrix. In situations where either the model is unknown or it is not possible to run enough experiments to estimate all parameters of an assumed model, this criterion is considered as a viable tool in the task of design selection. This paper deals with the design space associated with n factors, each of which can take two levels. We exhibit minimax distance designs that compare favorably with designs chosen to do well on classical grounds.

Journal Title

Journal of Statistical Planning and Inference

Volume

44

Issue/Number

2

Publication Date

1-1-1995

Document Type

Article

Language

English

First Page

249

Last Page

263

WOS Identifier

WOS:A1995QP79100009

ISSN

0378-3758

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