This paper studies minimally-supported D-optimal designs for polynomial regression model with logarithmically concave (log-concave) weight functions.
Many commonly used weight functions in the design literature are log-concave.
We show that the determinant of information matrix of minimally-supported design is a log-concave function of ordered support points and the D-optimal design is unique. Therefore, the numerically D-optimal designs can be determined e¡Óciently by standard constrained concave programming algorithms.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0629105-143720 |
| Date | 29 June 2005 |
| Creators | Lin, Hung-Ming |
| Contributors | Mei-Hui Guo, Mong-Na Lo Huang, 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-0629105-143720 |
| Rights | unrestricted, Copyright information available at source archive |
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