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.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0728103-143737 |
| Date | 28 July 2003 |
| Creators | Chou, Chao-Jin |
| Contributors | Grace Shwu-Rong Shieh, Mong-Na Lo Huang, Chwen-Ming Chang, Fu-Chuen Chang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0728103-143737 |
| Rights | unrestricted, Copyright information available at source archive |
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