Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1148814 | Journal of Statistical Planning and Inference | 2012 | 9 Pages |
Abstract
We give a new characterization of Elfving's (1952) method for computing c-optimal designs in k dimensions which gives explicit formulae for the k unknown optimal weights and k unknown signs in Elfving's characterization. This eliminates the need to search over these parameters to compute c-optimal designs, and thus reduces the computational burden from solving a family of optimization problems to solving a single optimization problem for the optimal finite support set. We give two illustrative examples: a high dimensional polynomial regression model and a logistic regression model, the latter showing that the method can be used for locally optimal designs in nonlinear models as well.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Jay Bartroff,