Saturated locally optimal designs under differentiable optimality criteria
Statistics Theory
2014-12-01 v1 Statistics Theory
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.
Cite
@article{arxiv.1411.7601,
title = {Saturated locally optimal designs under differentiable optimality criteria},
author = {Linwei Hu and Min Yang and John Stufken},
journal= {arXiv preprint arXiv:1411.7601},
year = {2014}
}
Comments
Published in at http://dx.doi.org/10.1214/14-AOS1263 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)