On Optimality of Designs with Three Distinct Eigenvalues

  • M. R. Faghihi
  • E. Ghorbani
  • G. B. Khosrovshahi
  • S. Tat
Keywords: Optimal designs, Designs with three eigenvalues, D-optimal, E-optimal, $\Phi_p$-optimal, KKT conditions, Group divisible designs


Let ${\cal D}_{v,b,k}$ denote the family of all connected block designs with $v$ treatments and $b$ blocks of size $k$. Let $d\in{\cal D}_{v,b,k}$. The replication of a treatment is the number of times it appears in the blocks of $d$. The matrix $C(d)=R(d)-\frac{1}{k}N(d)N(d)^\top$ is called the information matrix of $d$ where $N(d)$ is the incidence matrix of $d$ and $R(d)$ is a diagonal matrix of the replications. Since $d$ is connected, $C(d)$ has $v-1$ nonzero eigenvalues $\mu_1(d),\ldots,\mu_{v-1}(d)$.
Let ${\cal D}$ be the class of all binary designs of ${\cal D}_{v,b,k}$. We prove that if there is a design $d^*\in{\cal D}$ such that (i) $C(d^*)$ has three distinct eigenvalues, (ii) $d^*$ minimizes trace of $C(d)^2$ over $d\in{\cal D}$, (iii) $d^*$ maximizes the smallest nonzero eigenvalue and the product of the nonzero eigenvalues of $C(d)$ over $d\in{\cal D}$, then for all $p>0$, $d^*$ minimizes $\left(\sum_{i=1}^{v-1}\mu_i(d)^{-p}\right)^{1/p}$ over $d\in{\cal D}$. In the context of optimal design theory, this means that if there is a design $d^*\in{\cal D}$ such that its information matrix has three distinct eigenvalues satisfying the condition (ii) above and that $d^*$ is E- and D-optimal in ${\cal D}$, then $d^*$ is $\Phi_p$-optimal in ${\cal D}$ for all $p>0$. As an application, we demonstrate the $\Phi_p$-optimality of certain group divisible designs. Our proof is based on the method of KKT conditions in nonlinear programming.

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