A New Characterization of Elfving's Method for High Dimensional Computation
Abstract
We give a new characterization of Elfving's (1952) method for computing coptimal 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 coptimal 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.
 Publication:

arXiv eprints
 Pub Date:
 October 2011
 arXiv:
 arXiv:1110.6623
 Bibcode:
 2011arXiv1110.6623B
 Keywords:

 Mathematics  Statistics Theory;
 Statistics  Methodology;
 62K05 (Primary) 62J05 (Secondary)
 EPrint:
 2 figures