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Robust A-optimal designs for mixture experiments in Scheffe' models

A mixture experiment is an
experiments in which the q-ingredients are nonnegative
and subject to the simplex restriction on
the (q-1)-dimentional probability simplex. In this
work , we investigate the robust A-optimal designs for mixture
experiments with uncertainty on the linear, quadratic models
considered by Scheffe' (1958). In Chan (2000), a review on the
optimal designs including A-optimal designs are presented for
each of the Scheffe's linear and quadratic models. We will use
these results to find the robust A-optimal design for the linear
and quadratic models under some robust A-criteria. It is shown
with the two types of robust A-criteria defined here, there
exists a convex combination of the individual A-optimal designs
for linear and quadratic models respectively to be robust
A-optimal. In the end, we compare efficiencies of these optimal
designs with respect to different A-criteria.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0728103-143737
Date28 July 2003
CreatorsChou, Chao-Jin
ContributorsGrace Shwu-Rong Shieh, Mong-Na Lo Huang, Chwen-Ming Chang, Fu-Chuen Chang
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0728103-143737
Rightsunrestricted, Copyright information available at source archive

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