Abstract
We develop general theory for finding locally optimal designs in a class of single-covariate models under any differentiable optimality criterion. Yang and Stufken [Ann. Statist. 40 (2012) 1665-1681] and Dette and Schorning [Ann. Statist. 41 (2013) 1260-1267] gave complete class results for optimal designs under such models. Based on their results, saturated optimal designs exist; however, how to find such designs has not been addressed. We develop tools to find saturated optimal designs, and also prove their uniqueness under mild conditions.
Original language | English (US) |
---|---|
Pages (from-to) | 30-56 |
Number of pages | 27 |
Journal | Annals of Statistics |
Volume | 43 |
Issue number | 1 |
DOIs | |
State | Published - Feb 1 2015 |
Keywords
- Chebyshev system
- Complete class
- Generalized linear model
- Locally optimal design
- Nonlinear model
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty