Two-level D- and A-optimal designs of Ehlich type with run sizes three more than a multiple of four
By: Mohammed Saif Ismail Hameed , Eric D. Schoen , Jose Nunez Ares and more
For the majority of run sizes N where N <= 20, the literature reports the best D- and A-optimal designs for the main-effects model which sequentially minimizes the aliasing between main effects and interaction effects and among interaction effects. The only series of run sizes for which all the minimally aliased D- and A-optimal main-effects designs remain unknown are those with run sizes three more than a multiple of four. To address this, in our paper, we propose an algorithm to generate all non-isomorphic D- and A-optimal main-effects designs for run sizes three more than a multiple of four. We enumerate all such designs for run sizes up to 19, report the numbers of designs we obtained, and identify those that minimize the aliasing between main effects and interaction effects and among interaction effects.
Similar Papers
Studying Optimal Designs for Multivariate Crossover Trials
Methodology
Finds best ways to test many medicines at once.
On the E(s^2)-optimality of two-level supersaturated designs constructed using Wu's method of partially aliased interactions on certain two-level orthogonal arrays
Methodology
Makes experiments more efficient and accurate.
On the E(s^2)-optimality of two-level supersaturated designs constructed using Wu's method of partially aliased interactions on certain two-level orthogonal arrays
Methodology
Makes experiments more efficient and accurate.