On optimality of designs with three distinct eigenvalues
arXiv:1205.5876
Abstract
Let $\D_{v,b,k}$ denote the family of all connected block designs with treatments and blocks of size . Let $d\in\D_{v,b,k}$. The replication of a treatment is the number of times it appears in the blocks of . The matrix is called the information matrix of where is the incidence matrix of and is a diagonal matrix of the replications. Since is connected, has nonzero eigenvalues . Let $\D$ be the class of all binary designs of $\D_{v,b,k}$. We prove that if there is a design $d^*\in\D$ such that (i) has three distinct eigenvalues, (ii) minimizes trace of over $d\in\D$, (iii) maximizes the smallest nonzero eigenvalue and the product of the nonzero eigenvalues of over $d\in\D$, then for all , minimizes over $d\in\D$. In the context of optimal design theory, this means that if there is a design $d^*\in\D$ such that its information matrix has three distinct eigenvalues satisfying the condition (ii) above and that is E- and D-optimal in $\D$, then is -optimal in $\D$ for all . As an application, we demonstrate the -optimality of certain group divisible designs. Our proof is based on the method of KKT conditions in nonlinear programming.
14 pages, final version