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	07 Jul 2015
Event title	30th International Workshop on Statistical Modelling (IWSM)
Event type	Conference
Location	AustriaShow on map