Majorization framework for balanced lattice designs
Statistics Theory
2007-06-13 v1 Statistics Theory
Abstract
This paper aims to generalize and unify classical criteria for comparisons of balanced lattice designs, including fractional factorial designs, supersaturated designs and uniform designs. We present a general majorization framework for assessing designs, which includes a stringent criterion of majorization via pairwise coincidences and flexible surrogates via convex functions. Classical orthogonality, aberration and uniformity criteria are unified by choosing combinatorial and exponential kernels. A construction method is also sketched out.
Cite
@article{arxiv.math/0603082,
title = {Majorization framework for balanced lattice designs},
author = {Aijun Zhang and Kai-Tai Fang and Runze Li and Agus Sudjianto},
journal= {arXiv preprint arXiv:math/0603082},
year = {2007}
}
Comments
Published at http://dx.doi.org/10.1214/009053605000000679 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)