Title

Minimax Distance Designs In Two-Level Factorial Experiments

Keywords

62K05; Bayesian design; Computer experiments; Design optimality criteria; Two-level fractional factorial design

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. © 1995.

Publication Date

4-1-1995

Publication Title

Journal of Statistical Planning and Inference

Volume

44

Issue

2

Number of Pages

249-263

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/0378-3758(94)00047-Y

Socpus ID

0041541641 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0041541641

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