Computing D-optimal Size-and-Cost Constrained Designs of Experiments

Description

In this paper, we study the problem of D-optimal experimental design under two linear constraints, which can be interpreted as simultaneous restrictions on the size and on the total cost of the experiment. For computing a size-and-cost constrained approximate D-optimal design, we propose a “barycentric” algorithm with sequential removal of redundant design points. We analytically prove convergence results about the barycentric algorithm and numerically demonstrate its favourable properties compared to competing methods.

Period	30 Jun 2015
Event title	PROBASTAT 2015, The Seventh International Conference on Probability and Statistics
Event type	Conference
Location	SlovakiaShow on map