Abstract
We extend the approach in [Ann. Statist. 38 (2010) 2499-2524] for identifying locally optimal designs for nonlinear models. Conceptually the extension is relatively simple, but the consequences in terms of applications are profound. As we will demonstrate, we can obtain results for locally optimal designs under many optimality criteria and for a larger class of models than has been done hitherto. In many cases the results lead to optimal designs with the minimal number of support points.
Original language | English (US) |
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Pages (from-to) | 1665-1681 |
Number of pages | 17 |
Journal | Annals of Statistics |
Volume | 40 |
Issue number | 3 |
DOIs | |
State | Published - Jun 2012 |
Externally published | Yes |
Keywords
- Locally optimal
- Loewner ordering
- Principal submatrix
- Support points
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty